Software Testing Trends To Follow Closely In 2022

In today’s era of technological advancement, the world of software development and testing is also inventing innovative ways to integrate new technologies such as Artificial Intelligence, Machine Learning, and Big data to deliver quality software to customers. IT organizations must keep up with emerging software testing trends to keep innovative processes and innovations on par. The role of Quality Assurance (QA) in software development continues to evolve with industry trends. After a dramatic shift, QA evolved from manual test execution to a strategic function, becoming a top priority for his CIO today. As software testing continues to be a critical factor in the successful delivery of projects and products, in this blog, let’s uncover the major trends in software testing that practitioners can’t afford to miss. QA is becoming less of an afterthought. According to the World Quality Report for 2021-2022, the QA function should contribute to business growth and improved results. The report also highlights that company executives emphasize quality assurance more than ever. This serves the purpose of shifting to the left and speeding up project delivery and quality. The ability to quickly scale automation, improve test environment management, and ensure an approach to enhancing tester skills within an organization are just a few of the trends you need to keep up to date to be successful. Let’s look into the upcoming software testing trends that developers need to be aware of. Upcoming Software Testing Trends  The following are some of the best upcoming software testing trends to look forward to beyond 2022: Testing Centers of Excellence (TCoE) The business community is increasingly establishing Testing Excellence Centers to meet challenges such as shrinking budgets and different test delivery models. Other factors, such as poor test performance due to different test processes across regions, locations, and teams, and underutilized resources, drive the need to set up a TCoE.  This allows for his centralized QA function, consistent processes, detailed metrics across projects, and consistent delivery to improve customer satisfaction. Automated Testing There is a transition from licensed software tools to open-source tools. Organizations that demonstrate experience with open-source tools will thrive in emerging markets.  However, it is crucial to demonstrate that the chosen tool works well in the client environment before starting any automation work. This creates customer confidence in the proposed solution, resulting in better execution speed, lower costs, faster regression cycles, and, therefore, superior quality. Digital Transformation The increasing adoption of digital transformation programs such as DevOps has caused organizations to rethink quality assurance from a digital perspective. As a result, teams are more closely connected because QA can speed things up while maximizing efficiency. But continuous development and delivery go awry without a robust QA strategy.  As a result, DevOps was merged with his QA, resulting in a new framework called QAOps. QAOps maintains software quality by approaching software with a DevOps mindset. Exploratory Testing Simply put, exploratory testing is the answer to building quality solutions without automation. One of the keys to exploratory testing, the charter, essentially consists of establishing a clear mission for the session under test.  As a tester, your job is to ask questions about the user’s story and define the scope of the mission as an investigator. The primary key to exploratory testing is allowing users to be creative in finding new bugs not found in non-scripted tests. Mobile Testing  Mobile Testing Lab should be set up with different operating systems. However, managing various devices and operating systems remains a challenge. Experience with mobile testing is critical to the overall success of the QA feature as it involves multiple mobile devices.  Additionally, mobile testing is becoming more and more critical to all customers. Therefore, setting up a mobile test lab to take over device management is advantageous in today’s business environment. Security Testing With the rise of remote work, security testing has become a priority for all businesses, but cloud-based testing raises security concerns. Since this is a specialized function, employees and partners with security expertise are essential to building a comprehensive testing organization.  Standard security requirements include confidentiality, integrity, authentication, availability, authorization, and non-repudiation. This professional skill will continue to be in high demand and will play an essential role in security’s overall quality and effectiveness. Early Detecting Of Errors  Today, IT organizations spend the majority of their budgets on quality assurance. Involving the QA team early in the software development lifecycle is essential to ensure that budget increases are viable. The sooner defects are identified, the lower the cost of fixing them and the overall cost of quality.  The key to shifting left is measuring the effectiveness of the change and determining whether it meets end-user expectations.  Conclusion  As we live in a technology-driven world, businesses must stay informed of upcoming software testing technology trends. New-age technologies such as AI and ML are present in the industry and will continue to be trends.  Meanwhile, mobile test automation is expected to dominate the market, with hyper-automation expected to top the charts in 2022. Leverage next-generation software testing services to ensure your products are fully functional and deliver superior CX to your end users. The post Software Testing Trends To Follow Closely In 2022 appeared first on ONPASSIVE.
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Key Digital Marketing ROI Metrics You Should Know

Digital marketing KPIs or Key Performance Indicators are quantifiable goals that help you track and measure your success. In a changing marketing environment like today’s era of digital disruption, planning for KPIs in the short and long term is becoming increasingly important for modern businesses. KPIs are a digital way to help marketers set expectations and demonstrate that their work is making a positive impact. To an outsider, it may is it not. Measuring progress for digital campaigns is usually easier than offline ones. An innovative marketing plan is essential for measuring and tracking progress and demonstrating value. This blog aims to set KPIs for digital marketing so businesses can measure what matters at the moment in a way that all parties can agree on. Learn about negotiating KPIs, budgeting, and incorporating KPIs into the Smart Insights RACE framework. Importance of Tracking Digital Marketing ROI You cannot manage what you cannot measure. This is especially true when it comes to digital marketing. This is why understanding your ROI metrics for digital marketing is so important.  Knowing and understanding these metrics is very important, even running a digital marketing campaign. It helps you measure the success of your campaigns and optimize them for better results. Overall, tracking the right metrics can help you make better-informed decisions that can help you improve your campaigns and ultimately drive more sales. Your digital marketing plan should track your return on investment (ROI). ROI is a measure of return on spending and indicates whether your marketing investment has paid off. If the ROI is positive, you’re on the right track. If not, you need to rethink your marketing strategy. Digital marketers want to assess ROI over the long term, but they may also want to evaluate ROI on a campaign-by-campaign basis. To do this, you need to know which digital marketing metrics to use. In this post, we’ll explore some key ROI metrics for digital marketing and how to use them to measure your return on investment. Metrics For Highest Digital ROI The following are some of the top key KPI metrics that businesses should know in 2022: Cost Per Lead (CPL) Cost per lead is a metric that measures how much it costs to generate a new lead. To calculate your CPL, divide your total marketing spend by the number of new leads. For example, if you spent $500 on a campaign that generated 50 new leads, your CPL would be $500/$50, or $500 per lead. If your CPL is too high, you are spending a lot of money to acquire new leads, and you need to find ways to improve your campaigns. On the other hand, a low CPL means your campaign is performing well and generating new leads at a relatively low cost. Either way, CPL is the metric you need to track to make informed decisions about your digital marketing campaigns. Average Sale Price Average Selling Price is a relatively simple metric, but it can help you calculate your digital ROI. The average selling price is the average gross profit of a sale. Sum the total sales for a given period and divide by the number of sales. Averaging allows you to account for price differences due to sales, discounts, and product variations. Customer Lifetime Value Customer Lifetime Value (CLV) measures how much a customer is worth to a company throughout their time as a customer. To calculate CLV, multiply the average revenue you make from your customers in a year by the average number of years a customer stays with your company. Helps calculate her ROI of long-term marketing. Then subtract the cost of acquiring one customer from that number. The formula is (average annual revenue from a single customer x average number of years as a customer) – customer acquisition cost = CLV. Lead Close Rate  Lead close rate is the percentage of leads that are closed. H. They buy. To find the lead win rate, divide the total number of leads by the number of closed leads. Then multiply it by 100 to get a percentage.  You can use the lead win rate as part of your digital ROI calculation using the following formula:[(number of leads x lead close rate x average sale price) – the cost of marketing] / cost of marketing x 100 = ROI. Conversion Rate Conversion Rate is the percentage of visitors who convert, such as making a purchase or signing up for your email list. This metric is similar to the close rate. While the lead close rate can be measured over time, the conversion rate is typically used for specific campaigns. For conversion rate metrics, conversions can come from something other than existing leads. To find your conversion rate, divide the number of clicks by the number of conversions. Cost Per Click Your cost-per-click (CPC) is the amount you pay when someone clicks on your cost-per-click ad. To calculate CPC, determine the total cost of clicks over some time. Then divide this by the number of clicks received. Using Google Ads, you can see his CPC data in Google Analytics. You can also use the CPC Calculator to calculate your CPC quickly. Under Acquisition, Google Ads, and Campaigns, you’ll find other helpful information about your ad campaigns. You need to focus on leads over CPC to get a positive ROI. But keep in mind that only some clicks are converted immediately. Conclusion  Choosing suitable KPIs is an essential skill for digital marketers and takes some practice to master. It will only work sometimes, but anticipating what you can achieve over time and measuring your performance will help you grow as a marketer. The post Key Digital Marketing ROI Metrics You Should Know appeared first on ONPASSIVE.
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How Blockchain And AI Can Help The Food Supply Chain?

Food supply chains are complex. Many people are involved in the process, from when someone plants a seed to when it is harvested, processed, and delivered to stores. Blockchain is being explored to track food from farm to fork, which could help keep food safer and give consumers more information about what they eat. This article explores how blockchain and AI can help the food supply chain. What is the food supply chain industry? The food supply chain industry is responsible for getting food from farms to consumers. It includes all the steps involved in producing, processing, packaging, and distributing food. The industry is a complex system involving many players, including farmers, processors, distributors, retailers, and restaurants. The food supply chain is a vital part of the economy and is crucial in ensuring people have access to safe and nutritious food. The industry employs millions worldwide and generates billions of dollars in economic activity. The world population is projected to reach 9 billion by 2050, and the demand for food is expected to increase by 70%. The food supply chain industry faces challenges in meeting the growing demand for food. The industry will need to find ways to produce more food with fewer resources. The food supply chain industry is also facing challenges from climate change. Extreme weather events are becoming more common and are disrupting production and distribution systems. The initiative must adapt to a changing climate to maintain a reliable food supply.  The food supply chain industry is vital to the global economy and critical in ensuring food security. The industry is facing challenges in meeting the growing demand for food, but it is also innovating and adapting to a changing world.  Some of the innovations that are transforming the food supply chain include the following: 1. Big data and analytics: Data is used to track food throughout the supply chain, from farm to table. This data can improve efficiency, identify issues, and track trends. 2. Blockchain: Blockchain is a digital ledger that can be used to track food throughout the supply chain. The technology can help to ensure food safety and traceability. 3. 3D printing: 3D printing creates food, including meat and vegetables. This technology has the potential to create custom foods and reduce waste. 4. Robots are used in farms and factories to plant, harvest, and process food. This technology can help to increase productivity and reduce labor costs. Role Of AI and Blockchain in the food supply chain industry The food supply chain industry is in a constant state of change and evolution. To keep up with the ever-changing landscape, the industry must adopt new technologies that can help streamline processes and improve efficiency. Two of the most promising technologies in this regard are artificial intelligence (AI) and blockchain. AI can be used in several ways to improve the food supply chain. For instance, it can track food items throughout the supply chain, from farm to table. This would allow for better tracing of contaminated products and help reduce food waste. AI can also be used to predict consumer demand, which would allow businesses to adjust their production levels accordingly. On the other hand, blockchain offers a secure and transparent way to track transactions throughout the food supply chain. This would allow all parties involved – from farmers to distributors to retailers – to see the entire process. This could help reduce fraud and corruption and increase transparency and trust between all parties involved. Ultimately, AI and blockchain are two technologies that can potentially transform the food supply chain industry. By adopting these technologies, businesses can become more efficient and responsive to consumer needs while increasing transparency and trust throughout the process. Pros and Cons of using AI and Blockchain in Food Supply Chains The food supply chain industry is under immense pressure to improve its efficiency and transparency. In recent years, the industry has turned to new technologies, such as artificial intelligence (AI) and blockchain, to help address these challenges. AI and blockchain can potentially transform the food supply chain, but they also come with risks and drawbacks. Pros: 1. AI can help optimize the food supply chain by reducing wastage, improving forecasting, and optimizing production schedules. 2. Blockchain can create a more transparent and efficient food supply chain by tracking food items from farm to table. 3. The combination of AI and blockchain can create a “smart contract” that can automatically execute transactions based on predetermined conditions (e.g., payment for delivery of goods). Cons: 1. AI and blockchain are still emerging technologies, so there needs to be more standardization and interoperability between different systems. 2. Blockchain technology is often associated with cryptocurrencies like Bitcoin, raising security and stability concerns. 3. Using AI and blockchain in the food supply chain could lead to job losses as automation increases.  Thus, AI and blockchain promise the food supply chain industry. However, it is essential to carefully consider the pros and cons of using these technologies before implementing them on a large scale. Real-life application of blockchain in the food supply chain industry There are many potential applications of blockchain in the food supply chain industry. For example, blockchain could track the origins of food items and ensure that they are safe and healthy to eat. Blockchain could also track food items moving through the supply chain, from farm to table. This would reduce waste and ensure food items are delivered fresh and in good condition. Blockchain could also create a digital marketplace for buying and selling food items. This would allow buyers and sellers to connect directly without going through intermediaries such as supermarkets or wholesalers. This would reduce costs and make it easier for small-scale farmers and producers to sell their products. Some companies are already implementing blockchain solutions in the food supply chain industry. For example, Walmart is piloting a blockchain project to track pork products in China. IBM is also working on a Food Trust project to create a blockchain-based global food tracing system.  It is still early days for blockchain in the food supply chain industry, but the potential applications are numerous. With the help of blockchain, we could see a more efficient, transparent, and cost-effective food supply chain that benefits everyone involved. Conclusion The potential for blockchain and AI to help the food supply chain is immense. By tracking food items from farm to table, we can ensure they are safe and high-quality. Additionally, blockchain can help reduce waste and fraud in the food supply chain, while AI can be used to predict trends and optimize production. Together, these technologies have the potential to revolutionize the food industry and make our food system more efficient and sustainable. The post How Blockchain And AI Can Help The Food Supply Chain? appeared first on ONPASSIVE.
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The Disadvantages Of Using AI Facial Recognition

Facial Recognition is a technology used for many different applications and purposes. From keeping track of someone’s movements to identifying them from security cameras, technology has become so widespread that we take it for granted. However, there are disadvantages to using AI facial recognition. Along with public concerns about the security risks involved with having your face scanned, the underlying algorithms used in Facial Recognition could be better. Sometimes, there is a margin of error in recognizing you or someone else. There are many facial recognition programs, but only some are as accurate as you think. This article discusses the disadvantages of using an AI-powered facial recognition program. What Is AI Facial Recognition? AI Facial Recognition is a technology that uses artificial intelligence to identify and track people’s faces. It can be used for security, marketing, or other purposes. There are many different types of AI facial recognition systems. Some use 2D images, while others use 3D models. Some plans only work with still images, while others can also track moving faces. Most AI facial recognition systems work by first identifying features in a face, such as the eyes, nose, and mouth. These features are then converted into numerical values called “feature vectors.” The system compares these feature vectors to a database of known faces and tries to find the best match. AI. Some AI facial recognition systems can also estimate a person’s age, gender, and ethnicity. Others can even detect emotions on a person’s face. Facial Recognition is often used for security purposes, such as identifying criminals or terrorists in a crowd. It can also be used for advertising, such as targeted ads based on a person’s age or gender. AI facial recognition is not perfect, and it can sometimes make mistakes. For example, it may mistake one person for another or fail to identify someone wearing sunglasses or a hat.  How does AI Facial Recognition work? Facial recognition technology has been around for a while, but it has only recently become widely available thanks to advances in artificial intelligence (AI). AI facial recognition works by mapping someone’s face and then comparing it to a database of faces. The technology can identify the person if there is a match. There are two main types of AI facial recognition: 2D and 3D. 2D systems use photos or videos to map a person’s face, while 3D systems use depth sensors to create a three-dimensional model of a person’s face. 3D systems are generally more accurate, but they are also more expensive. Facial recognition technology could be better. It can sometimes have difficulty distinguishing between similar-looking faces, and it can be fooled by things like eyeglasses or changes in hairstyle. However, it is getting better all the time, and it is likely that eventually, it will be challenging for anyone to avoid being identified by facial recognition technology if they are in a public place where it is being used. What are the Advantages of using AI Facial Recognition? There are many potential advantages to using AI facial recognition technology. For example, it could be used to help identify criminal suspects or to find missing persons. It could also be used in security applications, such as airports or other high-security areas. Additionally, AI facial recognition could provide personalized customer service by remembering a customer’s preferences and providing tailored recommendations. However, there are also several potential disadvantages to using AI facial recognition technology. One key concern is privacy; for example, individuals might not want their faces to be scanned and stored in a database. Additionally, there is the potential for misuse of AI facial recognition technology; for example, it could be used for mass surveillance or to target specific groups of people based on their appearance. Additionally, AI facial recognition technology is not perfect and can sometimes make mistakes, leading to negative consequences for misidentified people. Disadvantages of using AI Facial Recognition There are several disadvantages to using AI facial recognition, including: 1. False positives. AI facial recognition can sometimes identify a person as being someone they’re not. This can lead to innocent people being detained or arrested. 2. False negatives. AI facial recognition can also fail to identify a person who is present. This can result in criminals escaping detection or being misidentified as someone else. 3. Racial bias. Studies have shown that AI facial recognition systems are more likely to identify people of color than white people incorrectly. This problem is compounded by the fact that most training data sets used to develop these systems are predominantly white. 4. Invasion of privacy. Some believe using AI facial recognition amounts to an invasion of their privacy, allowing organizations to track and monitor individuals without their consent. 5. Diminished public trust. AI facial recognition can erode public confidence in institutions that use it, as it raises concerns about government surveillance and potential abuse. Limitations of Artificial Intelligence There are several disadvantages to using AI facial recognition, including: 1. Limited accuracy: AI facial recognition technology still needs to be 100% accurate and often produces false positives or negatives. This can lead to innocent people being wrongly accused or convicted and criminals escaping justice. 2. Biased results: AI facial recognition algorithms can be biased against certain groups of people, such as those with darker skin tones. This can result in discrimination and unfairness. 3. Invasion of privacy: AI facial recognition technology raises serious privacy concerns, as it allows for the mass surveillance of individuals without their knowledge or consent. 4. Security risks: If facial recognition data falls into the wrong hands, it could be used for identity theft, fraud, or other malicious activities. 5. Job losses: As AI facial recognition technology becomes more widespread, it could lead to job losses in the security and law enforcement industries as machines replace human workers. Conclusion AI facial recognition technology has the potential to do more harm than good. Not only is it biased and inaccurate, but it also invades our privacy and could be used to control and manipulate us. We should be cautious about how this technology is used and who has access to it. The post The Disadvantages Of Using AI Facial Recognition appeared first on ONPASSIVE.
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The Ultimate Guide To Designing A Spam Filtering System

Designing a spam filtering system is not an easy task. Spam filters are designed to identify and filter out unwanted emails from a user’s inbox; this can be accomplished through two different approaches: the first is to design a system that automatically learns from its mistakes, and the second is to set up rules for identifying spam. In this article, we will learn how to build our machine-learning algorithms for designing a spam filtering system. What is Spam Filtering System? A spam filtering system is software used to identify and filter out spam emails from a user’s inbox. It uses a set of rules or criteria to determine which emails are considered spam and will either delete them outright or move them to a separate folder. Many email providers now have some form of spam filtering, but users can also install third-party spam filters. Types of Spam Filtering System There are several types of spam filtering systems available to organizations. Check out the list: 1. Bayesian Filters: Bayesian filters use a statistical approach to identify spam messages. They analyze the content of emails and compare it to a database of known spam messages. Based on this analysis, they can provide a pretty good indication of whether an email is likely to be spam or not. 2. Blacklist Filters: Blacklist filters work by comparing the sender of an email against a list of known spammers. If the sender is on the list, their email is automatically considered spam and is blocked accordingly. 3. Whitelist Filters: Whitelist filters are the opposite of blacklist filters. They work by only allowing emails from senders who are on a pre-approved list. Any emails that come from outside of this list are automatically considered to be spam and are blocked. 4. Content-Based Filters: Content-based filters examine the actual content of an email and look for specific keywords or patterns typically associated with spam messages. If these keywords or patterns are found, the email is flagged as potentially spammy and subjected to further scrutiny. 5. Heuristic Filters: Heuristic filters use various criteria to identify spam messages. This can include things like examining the headers of an email to see if they look suspicious, checking for common misspellings often used by spammers, or looking for other red flags that might indicate that an email is a spam. 6. DNSBL Filters: DNSBL filters work by checking the sender’s IP address against a list of known spammers. If the IP address is on the list, the email is considered spam and blocked. 7. Sender Policy Framework (SPF) Filters: SPF filters work by checking the sender of an email against a list of approved senders. If the sender is not on the list, their email is considered spam and blocked. 8. DomainKeys Identified Mail (DKIM) Filters: DKIM filters work by checking the digital signature of an email against a list of approved signatures. If the signature does not match any on the list, the email is considered spam and blocked. How to Design a Spam Filtering System using machine learning algorithms? There are many different ways to design a spam filtering system, but one common approach is to use machine learning algorithms. These algorithms can be trained on data sets of known and non-spam emails and then used to classify new emails. Many machine-learning algorithms can be used for this task, including support vector machines, naive Bayes classifiers, and decision trees. Each algorithm has its strengths and weaknesses, so choosing the right one for your particular data set and application is essential. Once you have chosen an algorithm, you must train it on your data set. This process involves providing the algorithm with training examples, which it will use to learn the characteristics of spam and non-spam emails. Once the algorithm has been trained, it can be used to classify new emails. If you are unsure which algorithm to use or how to train it on your data set, many online resources can help you. There are also commercial software packages that offer ready-made solutions for spam filtering. Whatever approach you take, it is essential to remember that no spam filtering system is perfect, and there will always be some false positives (emails classified as spam when they are not) and false negatives (emails classified as non-spam when they are). However, by using a well-designed machine learning system, you can significantly reduce the amount of spam in your inbox. Conclusion Designing a spam filtering system can be daunting, but with the right guidance, it can be relatively easy. With a little effort, you can have a fully functioning system that will help you keep your inbox clean and organized. This guide has provided you with all the information you need to design your spam filtering system. The post The Ultimate Guide To Designing A Spam Filtering System appeared first on ONPASSIVE.
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The Best Techniques for Optimizing IT Costs

Understanding digital transformation is essential, given that information technology is transforming every industry worldwide. Digital transformation, according to Gartner, can encompass various activities, including IT modernization (such as cloud computing), digital optimization, and the creation of new digital business models. The market is flooded with tools and technology, making it difficult for businesses to discover, pick, and use the best ones to get the best outcomes. It can be challenging to keep up with the latest trends because they significantly impact business expenditures. For this reason, it’s crucial to employ proper cost optimization approaches to balance the prices of IT investment with technological advancement. Technology-based solutions are constantly complex because new technologies and services are always developed. The current trend is using shared services, open-source databases, and simple access to technologies like Kubernetes, containers, microservices, and the cloud. High-performing networks and auxiliary hardware systems become more and more necessary, and the overall cost ultimately suffers.  We now experience quick and frequent deployments due to the new agile working style. Operations have become more complicated, and deployment failures have grown. All of these factors have further boosted the technology’s complexity and price. The Changing Scenario Of IT Infrastructure Any IT system needs a network connection that is quick and dependable. Modern network innovations that handle multiple devices simultaneously, such as 5G connection, SASE (Secure Access Service Edge), and Internet of Things services, might lessen reliance on various network systems for optimal bandwidth. However, this might result in more sophisticated, technologically integrated solutions. Any business journey toward digital transformation has been significantly impacted by the development of hybrid IT and multi-cloud platforms. Older tools for comprehensive resolutions may seem outdated because they won’t be set up for the most recent changes. Full-stack management is more necessary for accurate problem identification when a system’s complexity rises due to its multi-functionality. The system’s complexity, security, effectiveness, and productivity under review are challenged due to these new trends. Additionally, as there will be a greater need for seamlessly managed systems and a greater number of applications, SLAs will become stricter and demand the highest levels of uptime and reliability.  Any downtime will have a negative impact on business and must be avoided at all costs or minimized. Cost optimization must therefore be a top focus. It can be accomplished by consolidating tools, automating processes, enhancing performance, increasing productivity, and preventing downtime. Best Practices for IT Cost Optimization The following are a few best strategies for IT cost optimization: Align Initiatives with Business Priorities Increased cost awareness, just-in-time provisioning, rightsizing, and auto-scaling are a few initiatives that positively affect your business performance. The bottom line profit will rise by reducing spending. However, it’s crucial to consider IT’s goal of promoting top-line growth. IT is frequently the main force behind expanding market penetration, cutting lead times, and stimulating innovation in the age of digital transformation. The main corporate goal of revenue growth may be compromised by only considering the expense side of the equation.  It’s crucial to regularly assess optimization efforts in comparison to these goals. Finding the proper cost, not the cheapest, is what “optimizing” cost refers to. Communication is a crucial factor to take into account in order to gain support from the business. It’s essential to communicate the goals and logic behind these activities. The best-laid plans can be derailed if there isn’t enough support for the changes you want to make. IT will be badly impacted if the business is not consulted, and the point that IT exists to help the company will be missed. Gain Awareness Of Your Hybrid It Environment Visibility of every component engaged in the service delivery is necessary for optimizing the cost of IT services. However, lacking this visibility is something that businesses do quite frequently. All service components have been moved to public cloud services or have been introduced there. The new norm for practically every firm is hybrid IT, which combines traditional on-premises data center operations with public cloud services. The placement was frequently opportunistic and not part of a thorough master plan (because of provisioning lead time, cost, security, etc.). Due to this, individual company services now frequently cross several platforms and service providers. In a similar vein, no solid hybrid IT strategy was employed to choose the management tools that were being deployed. Each provides a partial picture of the environment or a particular technology.  You need a platform that provides unified visibility and analysis for the entire environment if you want to comprehend how hybrid services are used and performed. Data collection and analysis are challenging and time-consuming due to silo limitations. Set Cost Structures Clearly You must establish the cost structure for your operating environment to accurately quantify cost savings. By dividing the cost into its parts, you can swiftly evaluate several options and ensure that the financial impact is highly important.  Without ongoing financial effect analysis, optimization efforts risk becoming purely technical exercises and losing sight of their primary objective, which is cost reduction. The cost per instance, transaction, user, etc., is the basis of the business agreement and subscription conditions for cloud-based services (IaaS, PaaS, or SaaS) provided by a third party.  The same holds for situations in which hosting and management of private infrastructure have been contracted out to a third party. However, in both cases, the structure may need to consider some of the agreement’s terms, such as volume-based discounts or term obligations. You often need to prepare a little more for traditional on-premise infrastructure hosted in your own data center.  You must define the costs of the following to assess the cost of running a system as a whole or the cost of each resource used by it: * specialized hardware parts * Hypervisor and OS * administration and upkeep work Usually, these three are the most expensive goods, so pay attention to them first. You might add the cost of network connectivity through shared resources, facilities (electricity, cooling, floor space), and software licenses for a more precise estimate. But it’s crucial to avoid becoming bogged down in constructing the ideal framework. Start with a basic model that can be improved over time by adding additional layers. Identify Inefficiencies Safely Every firm tries to avoid over-provisioning its infrastructure, but this is much easier said than done. The first difficulty is determining the best number of resources to allocate to new workloads and applications.  No matter how hard you try, you’ll probably still be off by a certain percentage. Even when you get it right the first time, the circumstances in which your applications are executed will likely change over time. Due to the seasonality of the business, workload intensity will change. The demand for services is affected by modifications to corporate operations. Adapting the resources allotted based on forecasts to the actual results is necessary. This implies that you still need to continuously assess, optimize, and decommission overused resources.  It’s vital to incorporate enough historical data to cover the entire business cycle of each evaluated task for finding surplus allocations. Align Costs Depending on Activity You can significantly lower the amount of waste by routinely reviewing the resources allotted and choosing appropriate courses of action. However, suppose there is no cost attached to how the various business units in an organization use IT resources. In that case, there is a risk that each team will keep using the resources to maximize its potential advantage, to the detriment of the organization as a whole. Charging each business unit according to its use is a simple technique to further guarantee the efficient use of resources. Once adopted, a well-designed allocation strategy requires little overhead and oversight since it promotes cost transparency in the workplace and encourages sensible business decisions across the board.  Conclusion  Any firm over IT cost optimization should never prioritize overgrowth prospects made possible by technology and information-driven initiatives.  The best course for organizations is to adopt new technologies, embed resource optimization into company culture, review and improve current processes, consolidate where practical, gather and analyze data from all relevant sources, and advance relentlessly along the path of digital transformation. The post The Best Techniques for Optimizing IT Costs appeared first on ONPASSIVE.
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Will Adoption of 5G Affect Cybersecurity?

With its faster data speeds, low latency, higher dependability, more network capacity, improved availability, and improved user experiences, the fifth-generation mobile network, or 5G, has completely transformed how people and devices communicate.  However, the deployment of 5G presents additional security issues, particularly network security risks. Organizations may successfully manage their investments and secure their data by recognizing the cybersecurity concerns involved with implementing 5G. The adoption of any new technology, meanwhile, is never without its difficulties. It won’t be possible to switch over instantly to 5G. Hardware changes for networks and devices are required to make them compatible with the new system. In the beginning, 5G will coexist with 4G networks while the physical infrastructure is upgraded.  At some point, 5G will be made available as an entirely software-based network that can be managed similarly to other current digital systems. Security Concerns with 5G Despite its many advantages, 5G will undoubtedly have its share of difficulties. The attack surface area and the cyber threat landscape will first grow significantly. Future upgrades will be implemented similarly to adding new software updates to a computer program or smartphone because 5G will likewise involve transitioning to a network that is almost entirely software. There will be several cyber vulnerabilities as a result, and security professionals will have to deal with updating technologies and practices to guarantee that a network is secure. While the globe prepares for 5G, more emphasis must be placed on installing suitable cybersecurity safeguards to ensure it happens without a hitch. Many businesses will need to modify their current cybersecurity strategies to deal with the developing technologies associated with 5G. How Will 5G Impact Cybersecurity? The newest 5G technology increases speed and dependability and offers several new opportunities. But the 5G network is mainly software-based. Building a 5G application on shaky cybersecurity grounds is equivalent. The following are a few most significant 5G security issues that need focus on: Distributed Denial-of-Service (DDoS) Attacks When core infrastructures fail, it has a significant impact, but the network architecture of 5G could make it worse. Recall that distributed denial-of-service (DDoS) attacks aim to degrade online performance by saturating the target with excessive traffic. According to Cisco, 15.4 million DDoS attacks will be worldwide by 2023. DDoS assaults frequently target internet-connected devices, so as the number of devices grows along with the rollout of 5G networks, DDoS threats could result in even more attacks that are more frequent and spread more quickly. The increased number of devices to maintain and the increased bandwidth to influence make these 5G security assaults more likely to be disastrous. As long as SaaS providers employ the proper credentials to defend against advanced DDoS and standard attacks, decentralized management solutions can significantly lessen the impact of DDoS attacks. Rapid Deployment of Vulnerable Technology Many billions of devices will be able to connect thanks to 5G technology. However, as more connected devices, there is also more vulnerability. Most of these devices lack built-in cybersecurity or are controlled by insecure programs. When infiltrated by a malicious actor, even gadgets like smart thermostats, door locks, and lights pose risks to physical security. These endpoints will be vulnerable to attacks as more manufacturers put these inadequately secured gadgets on the market because it is challenging to keep them routinely updated.  98% of Internet of Things (IoT) device traffic, according to a recent analysis, is unencrypted and exposes private and confidential information on the network. Additionally, medium-level or high-level assaults can affect 57% of IoT devices. They must secure all these connected endpoints to prevent hackers from breaking into other network sections, such as other linked IoT devices. Therefore, to have the best 5G security, it is advised to check the mitigation strategies for all devices on a network to ensure they are properly patched with newer operating systems, apps, and firmware. *  Network Slicing Slices, a component of 5G networks’ virtualized infrastructure, represent a further security problem. The numerous physical cell towers needed to support 5G will be equipped with Dynamic Spectrum Sharing (DSS), allowing them to operate multiple dedicated networks that can all share a single physical infrastructure.  In the future, these slices will house crucial utilities and services utilized by commercial and public networks. Each network slice may have unique qualities and identities, but this also implies that it will present unique dangers. Each slice within these cell towers can be attacked separately from a cyber threat perspective.  It is becoming more challenging to secure these autonomous slices that are part of the same physical infrastructure. It will probably call for the dynamic deployment of a cybersecurity solution. Integrating the essential defenses to protect a company against potential 5G assaults can be challenging. It’s critical to comprehend the consequences of how 5G will affect cybersecurity and start preparing your organization now. *  Software-defined Network Risks Another issue with 5G cybersecurity is the vulnerability of software-defined networks. With 5G, virtualized software will carry higher-level network operations instead of physical equipment. Since the software that controls these networks is attackable, this action will result in more vulnerabilities. These virtualized 5G networks will use the well-known common language of OS systems, and malicious people can exploit Internet Protocol. Networks in the past had actual choke points where all incoming and outgoing network traffic was directed. These choke points allowed for the deployment of security checks. This traffic will be dispersed throughout a network of digital routers with fewer chokepoints, decentralizing this necessary process and lessening the effectiveness of defenses against cyber threats. Due to the virtualized network services occurring at the virtual network edge in 5G’s software-defined networks, one security breach in one specific network area could jeopardize the entire network’s security. Conclusion  Outstanding productivity, creativity, and agility gains are made possible by 5G networks. Various digital transformation solutions, from edge computing to autonomous and automated manufacturing, as well as the ongoing transition to hybrid work paradigms, are driving its adoption. There is a chance for additional hazards and difficulties along with these advantages, though.  In light of this, businesses should think about security implications before anything else, as opposed to after. They can build a fabric-based security strategy that protects their technological investments by having closely linked, comprehensive policies. The post Will Adoption of 5G Affect Cybersecurity? appeared first on ONPASSIVE.
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Top 7 ways to find a sponsor for your event in 2022

Every event you plan needs sponsors. But with the competition, finding the money for sponsors can be challenging. But not to worry. This article will give you seven of the best ways to find a sponsor for your event in 2022. How to find a Sponsor: You will need to do some research and networking to find a sponsor for your event. Below are seven ways to help you find a sponsor for your event in 2022: 1. Create a Great Pitch When it comes to securing sponsorship for your event, a great pitch is essential. But what makes a great pitch? Here are some key elements: * A clear and concise description of your event. What is it, when is it taking place, and where will it be held? * A realistic assessment of your sponsorship needs. How much money do you need to secure, and what kind of in-kind support would be helpful? * An overview of your target audience. Who will be attending your event, and what interests do they have? * A detailed explanation of the benefits that sponsors will receive. Why should they invest in your event? * Craft a professional and well-designed proposal. This should include all the information listed above and additional details about your team and event concept. By following these tips, you can create a strong pitch that will increase your chances of securing the sponsorship you need to make your event a success. 2. Use Social Media There’s no doubt that social media has become one of the most powerful tools in marketing and networking. If you’re not using social media to find a sponsor for your event, you’re missing out on a huge opportunity. LinkedIn is a great platform to start with when it comes to finding sponsors. You can search for potential sponsors by industry, location, or company size. Once you find the sponsor, be sure to include a personal message explaining why you think they would be a good fit for your event. Use hashtags to search for companies or individuals who might be interested in sponsoring your event. For example, if you’re hosting a conference on digital marketing, you could search for #digitalmarketingsponsor or #sponsormydigitalmarketingevent. Twitter is another excellent platform for finding sponsors. Once you’ve connected with potential sponsors on Twitter, you must follow up with a phone call or email. Don’t be afraid to ask for what you need; remember, these companies want to gain exposure by sponsoring your event.  Be clear about what their sponsorship would entail and what benefits they would receive in return. By being proactive and using social media effectively, you’ll have no trouble finding the perfect sponsor for your next event! 3. Offer Product Samples If you’re looking to score a sponsor for your upcoming event, offering product samples is one of the best ways to sweeten the deal. This gives potential sponsors a taste of what they’re supporting and helps them envision their products being used by attendees. When crafting your sponsorship proposal, be sure to mention any product sampling opportunities you’re able to offer. If you have a large enough budget, you may consider hiring a professional marketing company to create custom sample packaging for your event. Regardless of your route, product samples can be a powerful tool in landing the sponsors you need to make your event a success! 4. Create a Proposal That Stands Out When finding a sponsor for your event, you must ensure that your proposal stands out from the rest. Do Your Research Before you even start reaching out to potential sponsors, you must do your research and know who would be the best fit for your event. There’s no use in trying to sell your event to a company that doesn’t align with your values or target audience. Keep It Concise Your proposal should be clear and concise, without any fluff or filler. Potential sponsors want to see that you know what you’re asking for and why their involvement would benefit both parties. Be Creative Don’t be afraid to think outside the box regarding your proposal. The more creative and unique your approach is, the more likely you will grab a sponsor’s attention. Offer Something In Return You must offer potential sponsors something in return for their support. Whether it’s exposure at your event or simply acknowledging their involvement, letting them know what they’ll get out of the deal will increase your chances of landing a sponsorship. 5. Write For The Sponsor’s Website Or Blog If you are a writer, one of the best ways to find a sponsor for your event is to write for the sponsor’s website or blog. This is a great way to get your name and event in front of the sponsor’s audience and can also help you build a relationship with the sponsor. When you’re writing for the sponsor’s website or blog, be sure to focus on topics that will be of interest to their audience. For example, if you’re sponsoring a food-related event, you could write about healthy eating tips, recipes, or new trends in the food industry. If you’re sponsoring an event for a fitness company, you could write about workout tips, healthy lifestyle habits, or new fitness products. Whatever topic you choose to write about, be sure to include information about your event so that readers will know how to get involved. You can also have a call-to-action at the end of your post, encouraging readers to visit your event website or register for your event. 6. Be a Good Publicist And Spread The Word About The Event As an event organizer, it’s your job to make sure that people know about it and that it runs smoothly. One of the best ways to do this is to find a sponsor. A sponsor can help promote your event and cover some of the costs associated with it. Here are some tips on how to find a sponsor for your event: Approach Local Businesses First: They may be more likely to support an event that’s taking place in their community.  Be Prepared To Negotiate: Be realistic about what you’re asking for and be prepared to compromise if necessary. Follow-Up After The Event: Remember to thank your sponsors for their support and let them know how the event went. This will help build goodwill for future events. 7. Be Persuasive In What You Ask When seeking sponsorship for your event, it is vital to be persuasive in what you ask. This means being clear about your event and why it would benefit the potential sponsor to get involved. You should also have a well-thought-out sponsorship proposal that outlines the benefits of sponsoring your event. Be sure to research potential sponsors before reaching out to them. It would help if you understood their business well and what they are looking to achieve through their sponsorship dollars. This will help you tailor your pitch to their specific needs and interests. Be confident in your request and be willing to negotiate if necessary. Remember, the worst thing a potential sponsor can say is no, so go for it. Conclusion Finding a sponsor for your event can be a breeze with the right approach. By following our tips and using the resources at your disposal, you’ll be well on your way to securing the funding you need to make your event a success. And who knows? Maybe 2022 will be the year your event is finally sponsored by that big company you’ve always dreamed of working with. The post Top 7 ways to find a sponsor for your event in 2022 appeared first on ONPASSIVE.
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Strategies to Migrate Towards Sustainable Green Cloud

Modern businesses explore new opportunities to use cloud computing as technology develops in order to collect more statistics and data and stay ahead of the curve. Cloud computing is one technological advancement that has provided ample opportunity for expanding many businesses and starting a journey toward digital transformation. The advantages of cloud computing versus on-premise infrastructure include lower investment risks, lower costs, more availability, and a shorter time to market. On the other hand, on-premise infrastructure entirely depends on high energy usage (servers and other hardware requirements).  In contrast to cloud computing, servers have bigger carbon footprints and use energy at varying rates. Compared to cloud data centers, on-premise servers are 29% less efficient in terms of power consumption. In order to aggregate computing and its flexibility to change workloads, cloud computing is now more energy-efficient, and CO2 emissions have been greatly decreased. The United States Environmental Protection Agency (EPA) and tech and telecom corporations have teamed up for 100% green power usage in response to concerns about excessive carbon emissions. Optimizing energy usage is one of cloud computing’s main issues, which is how green cloud computing came into existence. Designing, generating, and utilizing digital resources using cloud storage with a minor adverse environmental impact is known as “green cloud computing.” How Does Green Cloud Computing Work? Green cloud computing not only offers efficient infrastructure and processing, but it also conserves energy. Green computing is a technique for minimizing both the use of computing resources and environmental effects. The process of adopting this architecture in the data center es is known as green cloud computing. Every industry seeks to implement environmentally friendly practices into their industries to respond to increased energy consumption. Given its many benefits, cloud computing was welcomed by many IT companies, and it helped the environment by reducing the energy use of businesses’ data centers. On the other side, cloud computing does away with the need for a separate data center. It reduced data theft and loss by combining all processing and storage needs for a specific zone into a single data center with solid security. These procedures produce Green Cloud Architecture, improving energy efficiency and awareness of carbon emissions. Building a Green Area has as its goal lowering energy usage. Optimization of Green Cloud Computing Design, operational, and energy usage considerations are a few factors that go into green cloud computing, which has four main pillars. * Energy Resources: Where cloud infrastructure is fueled by renewable energy, cloud providers are in charge of this aspect. * Energy Efficiency: To make cloud infrastructure more energy-efficient, tech behemoths like Microsoft have employed efficient cooling strategies, such as submerging data centers in the ocean. * Number and Size of Servers: Businesses can increase the efficiency of their applications while lowering the number of servers, reducing storage costs and the carbon footprint. * Reducing Data Transfer: The required data can be decreased by enhancing the caching process, reloading only the necessary components, and prioritizing the mobile experience. Organizations can use these infrastructures, which are geared to reduce energy usage and carbon emissions. Best Strategies For Successful Migration Towards Sustainable Green Cloud To allow for the modification of IT infrastructure, cloud providers are going green and implementing net-zero practices (practices for carbon neutrality or reduction of carbon dioxide in the environment). Net-zero cloud migration would lessen environmental harm and create a long-lasting green cloud for the future. The following ate a few helpful tactics that can help achieve the green cloud goal: * Miniature Data Centres These data centers are dispersed worldwide and use less energy than typical ones because they are more numerous and more petite. These small data centers are transportable and aid in lowering reaction times, which decreases downtime. They are also capable of self-adaptation or self-scalability and have high service proximity. *  Virtualization Of Servers For Resource Management The issue of data centers’ excessive power usage can be solved by virtualization. Virtualization is to divide a single resource into several portions to utilize it more effectively (including energy). Data centers must create virtual infrastructures to run many operating systems and applications on fewer servers.  In the following ways, such virtualization directly affects energy efficiency: * This offers virtualized applications instant failover. * Resource distribution is controlled. * Significantly higher server utilization suggests a reduction in the need for more servers. *  Cloud Optimization With Rank-Based Microservices Businesses that value environmentally friendly cloud computing are implementing green cloud optimization. Due to the flexibility of service delivery, which must be updated for green cloud computing, cloud services are increasingly moving away from monolithic design and toward micro-services. Numerous interconnected micro-services are executed on cloud nodes. Less energy is consumed by generating a rank-based profile for these micro-services by providing containers and distributing them among various nodes before running cloud services. Due to the availability of containers and micro-services in the exact data center location, the response time is also shortened. *  Intelligent Resource Scheduling Using AI AI can aid in reducing power consumption by allocating resources intelligently, something the conventional technique lacked. Resource scheduling is crucial for lowering energy consumption because cloud customers’ requirements vary.  Resource scheduling is a major problem in data centers that an AI-enabled solution reschedules using intelligent decision-making capabilities. The idea of “green cloud computing” is being pursued to preserve our eco-culture. The green cloud not only reduces carbon emissions but also has the potential to save enormous amounts of money on energy.  It’s more important to identify energy-saving digital solutions, such as changes to infrastructure, data storage, deployment, etc., which will lower enterprise costs and assist cut carbon emissions. *  Effective Infrastructure Utilization with IaaS The optimal approach to using resources has always been as-a-service in the cloud, and IaaS is one supporting paradigm that gives IT services scalability and elasticity. The virtual machine (VM), which serves as the primary computing component in data centers, must use less energy. Moving loads to active hosts allow these VMs to be condensed into fewer hosts, and inactive hosts are disabled. Therefore, overall energy usage is decreased using the IaaS cloud. Conclusion  Because most businesses have either gone or are now going to the cloud. Committing to the transition to green cloud computing calls for strategic planning of eco-culture, resource allocation, development, and implementation. This fits all business requirements in addition to being an environmentally sustainable solution. Our goal is to become known as an energy-efficient corporation by creating better and more energy-efficient cloud architectures. We also support enhancing cloud computing procedures, participating in the green cloud, and training our staff on internal best practices. Contact us for a free consultation on how to go toward the green cloud. The post Strategies to Migrate Towards Sustainable Green Cloud appeared first on ONPASSIVE.
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Data Analytics – Is This The Next Phase Of Digital Transformation?

The most successful companies in the world are utilizing data at previously unheard-of rates, and the effects are evident in their P&L. According to research from The Business Application Research Center (BARC), businesses that effectively use their data enjoy an 8% average rise in profitability and a 10% average decrease in costs. These kinds of outcomes are what will drive the Business Intelligence industry to $24 billion in 2022.  According to Fortune Business Insights, the market for data analytics for businesses is predicted to reach $43 billion by 2028, growing at a compound annual growth rate (CAGR) of 8.7%. This expansion is fueled by quick digitization and data collecting, the high demand for data personalization, and the requirement to make data-driven business decisions. However, many businesses still face difficulties using all of their data. In this post, we’ll outline the advantages of data analytics, give examples of how enterprises utilize data science, and discuss solutions to common problems. What Is Data Analytics? Every day, businesses worldwide produce enormous amounts of data in the form of log files, web servers, transactional data, and customer-related data. Social networking websites have a vast amount of data in addition to this. Companies should use their created data to maximize value from their created data and make significant business decisions. Data analytics is what is driving this objective. Businesses employ a wide range of current devices and methods for data analytics. Discovering hidden patterns and undetected trends, finding correlations, and gaining insightful knowledge from vast datasets are all part of data analytics used to create business forecasts. As a result, your business operates more rapidly and efficiently. In a nutshell, this is data analytics for newcomers. Importance Of Data Analytics For Businesses  In today’s market trend, data drives any firm in many ways. Data Science, Big Data Analytics, and Artificial Intelligence are the three main themes in today’s fast-paced business. As more businesses use data-driven models to automate their business processes, the data analytics sector is growing quickly. Organizations increasingly use data analytics to support fact-based decision-making, implement data-driven models, and broaden their data-focused product offerings. Businesses produce tons of data, and data analytics is the key to unlocking hidden insights. Data analytics may help a firm in several ways, including customizing a marketing pitch for a particular client and recognizing and reducing business risks. Following are a few of the main advantages of data analytics for businesses: * More customer personalization * Various business procedures being made more efficient better information to make decisions * Improved security  * Risk reduction and  * Improved setback management To maximize the benefits of data analytics, a company must centralize its data in a data warehouse for simple access. Accelerating Digital Transformation With Data Analytics The top data analytics trends listed below can assist firms in 2022 and beyond as they deal with numerous changes and uncertainties: Scalable & Smarter Artificial Intelligence The business environment has changed significantly due to COVID-19, rendering old data useless. As a result, specific scalable and cutting-edge AI and machine learning methods that can analyze small data sets are taking over the market to replace conventional AI methods. Most manual jobs can be automated and reduced by combining AI and Big Data. These technologies safeguard privacy, are speedier, and have a far quicker return on investment. They are also very customizable. Leveraging Edge Computing For Faster Analysis Although many big data analytics solutions are available, the issue of inadequate ample data processing power still exists. Thus, the idea of quantum computing has been developed. Utilizing less bandwidth, computation has increased the speed at which large amounts of data can be processed. It has also improved security and data privacy through quantum mechanics laws. Decisions are made using quantum bits in a processor called Sycamore, which can answer a problem in under 200 seconds, making this significantly superior to classical computing. Hybrid Cloud Solutions & Cloud Computing One of the most significant data trends for 2022 is the rising use of hybrid cloud services and cloud computing. A hybrid cloud balances cost and security by combining public and private clouds to achieve higher agility. While private clouds are more secure but more expensive, public clouds are less expensive but offer less security. To do this, Artificial Intelligence and Machine Learning are employed. Hybrid clouds are transforming businesses because they offer a centralized database, data security, scalability, and much more for less money. Engineered Decision Intelligence Artificial intelligence that is utilized to make decisions is known as engineered decision intelligence. It covers a variety of decision-making processes and enables firms to get the insights they require to accelerate business operations.  Additionally, it includes applications for conventional analytics, artificial intelligence, and sophisticated adaptive systems. Decision intelligence is becoming increasingly popular in the industry nowadays. Engineering Decision Intelligence has the potential to assist enterprises in rethinking their decision-making processes when paired with compatibility and common data fabric. Or, to put it another way, designed decision analytics can help people make better judgments rather than replace them. Conclusion  Data analytics is now a crucial tool for the company. Data tells tales vital for businesses to comprehend their current situation and forecast future results.  Data enables businesses to comprehend the existing market and assess developments. Companies that apply data analytics improve their KPIs, earnings, and profit margins, which leads to improved outcomes. The industry leaders in online streaming and e-Commerce are the most prominent examples of how Big data and analytics is being used to expand businesses.  A large portion of Amazon’s retail success, which accounts for more than one trillion dollars in annual revenue, can be attributed to its recommendation engine, which links user activity with previous purchase information and trends to predict customer demands. 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Why is Cloud Document Management Essential for Businesses?

The popularity of the cloud is on the rise. The pandemic significantly boosted the gradual organizational shifts to the cloud during the previous decade. As lockdowns and orders to stay at home spread, the cloud became crucial for enterprises to function. All firms, regardless of their size or industry, use documents extensively. Businesses rely on records for various tasks, including contract execution, creating employee manuals, defining workflows, creating marketing materials and project proposals, publishing technical documents, sharing HR policies, creating training materials, drafting legal and compliance reports, and a host of other tasks. Documents have been moved from paper to digital format by digitization. But it hasn’t pushed document substitutes. Since it is now simpler to create papers, digitization has contributed to their growth. The necessity of the cloud forces the transfer of documents from on-premises servers to cloud servers. Data management has long been regarded as one of the most challenging commercial tasks. Because even one lost or damaged document can result in high costs for the organization, your business must have a specialized document management system. Thankfully, cloud document management exists, as do numerous other cloud-based options. Defining Cloud Document Management System  The concept of document management in the cloud goes well beyond simply automating paperwork. It lets users see, manage, and edit data from saved documents. File sharing is made simple with SaaS. Mobile devices and document control work best in the cloud environment. You could even include additional mobile applications (iOS or Android). Software for managing documents in the cloud enables more efficient resource use. Paper documents are scanned and saved in a database accessible from anywhere as file formats. A digital filing cabinet that is. With the help of cloud services, the data can remain available for as long as necessary. Software for managing documents in the cloud can significantly increase worker efficiency and comfort. These tools reduce instances where redundant copies of archived documents are made. Users can work remotely worldwide and collaborate on the same record during business hours. Reasons To Use Cloud Document Management System By itself, and with little or no direct human oversight, using a cloud-based document management system for your company can resolve various problems relating to your place of business. The time is now to consider upgrading your conventional, on-premise document management system to take advantage of the multiple advantages moving to cloud computing offers businesses of every size.  The following are a few compelling benefits that your business can experience from deploying a cloud document management solution: Safeguard Sensitive Data Cloud services frequently include automatic updates and patches and numerous availability zones for your data. They also probably have additional staff members devoted to securing data that is kept in or transferred to and from the cloud. Some cloud suppliers may even provide tailored solutions that are either built into or can be added onto your current cloud solution with minimal setup required on your organization’s end and are based on the requirements of highly regulated industries, such as finance. This is excellent for businesses unable or unwilling to devote significant personnel or technological resources to cybersecurity. Reliable Data Backup Cloud material is backed up dozens, hundreds, or even thousands of times, unlike an internal solution, guaranteeing that you don’t lose important data. You can use this knowledge to make wise judgments and keep things moving in the business.  If one of these facilities is down, your data and services are usually still available, thanks to the fact that many cloud providers keep backups in many data centers. This can promote business continuity and help you recover from disaster fast. Integrations Of Business Tools You must choose a technology that enables integration with other business tools and utility applications because we live in a technologically advanced era where everything is becoming digitized. Manual document management makes integration impossible; cloud document management makes integration possible. Using this technology, you may combine your business resources, including project management software, social networking platforms, marketing analytics tools, and CRM systems. This will improve performance and produce better results in addition to automating procedures, reducing workload, and saving time. Anywhere Access Many experts are leaving well-known sector centers in the age of remote work and establishing home offices abroad. Cloud services make it simpler for teams to work and communicate, whether physically present or not, giving your company greater flexibility in how it recruits and develops talent. Additionally, connectivity from wherever can make business operations go faster. Let’s imagine a delay in a time-sensitive process that requires a specific person or position to resume operations. If this process is in the cloud, the employee or someone in that capacity can complete their tasks even if they cannot get to the office on time. Your firm becomes more effective when it can handle these scenarios and react promptly to market forces and changes. Less Paperwork Do you want a room at your workplace filled to the brim with files and paperwork? It would help if you switched to a cloud-based or web-based document management solution because traditional document management has numerous restrictions and drawbacks. When you migrate to a cloud-based document management system, you will save time, resources, and money because this technology does not require additional expenses for printing, storing, and maintaining documents. Making your company’s operations paperless is an excellent method to reduce your company’s environmental impact further. Low Maintenance A cloud solution frequently indicates little to no hardware expenditures and regular, automatic system updates. Your IT personnel can concentrate on new projects, purchases, or reply to support tickets more quickly if some of these tasks, along with security and data backups, are delegated to another company or service.  A more resilient company benefits from an agile IT workforce, especially business continuity. Due to a cloud document management system’s reduced infrastructure and network complexity, these advantages are the bonus of not needing IT assistance. Conclusion  Adopting cutting-edge business technologies is essential for competing with your rivals in this fiercely competitive market. A cloud document management system is another such piece of technology that will help your business become paperless by moving everything online.  Additionally, it will prevent human errors while saving resources, labor, and time. Be sure to consider the technical aspects, customer service, pricing, and integration support before making a final decision. 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A Guide to Programming Languages For Artificial Intelligence

Artificial intelligence is a term that refers to the theory and development of computer systems able to perform tasks that are commonly associated with human intelligence and reasoning. AI programming is a broad field, and many different languages have been developed for various applications. This article will briefly overview some of the most popular languages and what they’re used for. Defining Programming Language A formal language known as a programming language defines a set of instructions that can be used to generate different types of output. In computer programming, algorithms are implemented using programming languages. There are many other programming languages, each with its features and capabilities. Some popular programming languages include Java, Python, and C++.  Different Types of Programming Languages for AI A few different types of programming languages can be used for AI purposes. Some of the more popular ones include Python, R, and Java. However, many other programming languages can be used for AI development, including C++, Prolog, Lisp, and Haskell. Let’s learn more about each language. Python is a popular high-level, general-purpose programming language. Guido van Rossum invented it in 1991. Python is easy to learn for beginners and has an extensive standard library that covers a wide range of programming tasks. Python is often used in scientific computing, artificial intelligence, machine learning, and web development. R is a free programming language and graphical package for statistical computing. Robert Gentleman and Ross Ihaka came up with the idea in 1993. R is popular among statisticians and data miners for its flexibility and power. R can be used for various statistical analyses, including linear and nonlinear modeling, clustering, time series, and multivariate analysis. A flexible and potent object-oriented programming language is Java. James Gosling developed it in 1995. Java is widely used in web development, desktop applications, Android apps, big data processing, and scientific computing. Java has a rich library set that provides many valuable functions for AI development.  Lisp is a long-standing favorite among AI researchers due to its powerful symbolic processing capabilities. It’s also very flexible, allowing programmers to define their own custom data types and operations. However, it can be challenging to learn due to its unusual syntax. Prolog is well suited for developing applications that require search or planning algorithms. Its declarative nature makes code more readable and accessible than imperative languages like C++ or Java. However, Prolog isn’t as widely used as other options on this list so less community support may be available. Haskell is a purely functional programming language suited for building AI applications. Its robust system helps prevent errors and makes code more reliable. Haskell’s laziness can make code more efficient by avoiding unnecessary computations.  C++ is a powerful object-oriented language widely used in applications where performance is critical, such as video games, 3D animation, and scientific computing. C++ has a rich set of libraries for AI development, including the Standard Template Library (STL) and the Boost C++ Libraries. Benefits Of AI-based Programming Languages to use when building a product When building a product, there are many factors to consider. One crucial factor is the programming language you will use. In recent years, there has been a surge in the popularity of AI-based programming languages. These languages are designed to make it easier for programmers to create artificial intelligence applications. There are many benefits to using an AI-based programming language when building a product. Some of the benefits of using an AI-based programming language include the following: 1. Increased Efficiency: AI-based programming languages are designed to be more efficient than traditional languages. This means that you can build your product faster and with less code. 2. Better User Interfaces: AI-based programming languages often have better user interfaces. This makes it easier for users to interact with your product and get the desired results. 3. More Intelligent Code: AI-based programming languages allow you to write more intelligent code. This means your product will be more effective and efficient at solving problems and accomplishing tasks. 4. Greater Flexibility: AI-based programming languages are often more flexible than traditional languages. This means you can easily add or remove features from your product without having to rewrite large amounts of code. 5. Easier to Learn: Many AI-based programming languages are more accessible to learn than traditional languages. This makes it easier for new programmers to develop products using artificial intelligence. Drawbacks Of AI-based Programming Languages to use when building a product There are many different programming languages, each with unique features and benefits. However, some significant disadvantages must be considered when developing products using artificial intelligence (AI). Firstly, AI-based programming languages can be highly complex and challenging to understand. This can make the development process very slow and frustrating and increase the likelihood of errors. Secondly, these languages often require much processing power and memory to run effectively. This can make them unsuitable for smaller devices such as smartphones or tablets. Finally, developing products using AI-based programming languages can be prohibitively expensive. This is due to the need for specialist hardware and software, as well as the expertise of experienced developers. Conclusion Dozens of different programming languages can be used for artificial intelligence development. This guide has looked at some of the most popular options and highlighted their key features. Ultimately, your best language will depend on your specific needs and preferences. However, we hope this guide has given you a good starting point to make your decision. The post A Guide to Programming Languages For Artificial Intelligence appeared first on ONPASSIVE.
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Five Forces that are Shaping the Future of the Workforce

How we operate or function, including technology and employee experience, is undergoing a dramatic change for various reasons. Human work is being replaced by automation and “thinking machines,” changing the abilities that employers are searching for in candidates. Our list of occupations with the most significant growth serves as a harsh reminder of how the epidemic has accelerated the digitalization of the world economy. The Fourth Industrial Revolution was already driving up demand for engineering and Artificial Intelligence positions. The growth of our working practices can be highly unsettling, especially in light of rumors regarding the expected loss of jobs owing to automation and other changes brought about by Artificial Intelligence (AI), Machine Learning, and autonomous systems. But the future of work is more than just automation and changing employment trends. Upcoming Transitions In The Workplace  Businesses are experiencing significant upheavals as Industry 4.0 and a digital-first economy takes hold. Before companies can adjust to the new reality, they are smacked by another significant disruption: the evolving character of the workforce and the workplace. Workplaces have been beset by skill shortages for more than ten years, particularly in developing technology. Recently, this talent shortage has gotten worse. The gap between skill development and technological advancements is growing. Leading businesses go above and beyond to find talent. They boost HR and create aggressive head-hunting plans and budgets. They also implement formal training and development programs to improve staff skill sets. However, hiring talent alone is insufficient. Businesses experience turbulence due to the unpredictable nature of a changing workforce. The only companies that can compete are those adaptable to changing conditions. Forces shaping the future workforce Complex and conflicting influences will shape the future workforce. Future employment patterns will be influenced by disruptive technologies, shifting global economic power dynamics, climate change, and new business models, which will affect every industry. The following are the key forces that are transforming and changing the future of the workforce: Innovation In Technology How we live and work is evolving due to Big data, Artificial Intelligence (AI), robotics, the cloud, automation, and the Internet of Things (IoT). Big data helps us analyze the information we receive; the cloud transforms how information is stored and obtained. AI and IoT create intelligent factories and buildings to increase people’s safety and productivity. Automation and robotics force us to reevaluate traditional roles and how they can be improved.  New digital technologies may account for over two-thirds of the potential productivity increase in significant economies over the ensuing ten years. In practice, some occupations will be automated, many more will be created, and nearly every job will alter to fit the job environment of the twenty-first century.  Disruptive technologies’ relentless march has given rise to worries that automation would undercut human labor. These worries need to be addressed by stakeholders who can explain how technology supports concepts like equity, equality, inclusion, responsibility, transparency, and accountability. Bringing Diversity To Workplace  It is essential to create a diversified workforce. There is little doubt that businesses with varied workforces perform better than those without diverse workforces. Thus this presents a clear opportunity.  Employers should create particular recruitment and hiring plans for diverse candidates, then keep them on staff by giving them chances to advance their education and careers and take on leadership responsibilities. Businesses that genuinely commit to diversity will continue to be relevant and competitive in the future. Shifts In Global Economic Power  India has recently implemented business-friendly regulations to ensure that conducting business is simple in the nation and to promote economic progress. With 34% of the population in this age bracket, India also has the largest millennial market in the world.  According to reports, 56% of recruits in 2022 are predicted to be freshers with 0–5 years of experience. This reflects the high demand brought on by the expansion of already-existing professions and the emergence of new ones. The nation’s job prospects are expanding dramatically due to substantial expansion in sectors like digitalization and automation, shifting supply chains, growing wages, and a greater focus on sustainability, health, and safety. India is predicted to have rapid growth during the following three decades, with average GDP growth of 5% per year, making it one of the world’s fastest-growing economies. For international corporations aiming to diversify their production, the government likewise pursues “production-linked incentives.” If these incentives are successful, more high-tech and well-paying jobs will be created within the boundaries of India. Demographic shifts in the working population In the upcoming decades, the workforce will comprise many different generations. Workplaces will employ up to three generations at once as a result of later retirement ages and a significant increase in the millennial population in the workforce, which is predicted to reach 75% by 2025. Managing this will require leaders. Building cohesive and cooperative teams that promote better culture and performance requires bridging the communication gap across generations, taking advantage of millennials’ technology knowledge, and considering different expectations. In contrast, the issue in many developing economies, like India, is not merely a shortage of skills but also a mismatch between skill sets. This talent mismatch could have adverse effects on the workforce of the future. Upskilling the current workforce and giving them the tools they need to be prepared for Industry 4.0 is urgently required for these rising nations. Depletion Of Resources And Climate Change Climate change has an impact on occupations in addition to the environment. Professionals from various industries, including urban planners, technologists, engineers, surgeons, financial planners, and farmers, will likely see their fields influenced by climate change.  Worldwide efforts to reduce greenhouse gas emissions are pushing nations to switch to inexpensive renewable energy sources to boost their economies. In many economies, adopting sustainable technologies has boosted socioeconomic benefits, paving the way for the global effort to achieve zero emissions. Companies are committing to a greener working paradigm as innovative technology improves energy-saving, flexible working methods that prioritize worker safety in hazardous situations.  According to economists, the attention paid to climate change has made green economy occupations more appealing. The future economy is predicted to be giant, with nearly 30 million jobs directly connected to renewable energy and efficiency. Conclusion To enhance the employee experience, businesses will need to put a strong emphasis on diversity, accessibility, and inclusivity when designing the workplace of the future. Companies will stop focusing on creating an “office culture” with foosball tables and beanbag chairs. Instead, they will concentrate on fostering relationships among a dispersed workforce, granting employees the freedom to work effectively and providing the resources required to complete their tasks. Management techniques will need to change as “managing by walking around” will no longer work for the company. Employees will need to get acquainted with new tools that may be required for the future workplace, such as virtual workspaces and VR eyewear. The workforce is prepared for substantial change, and the future workplace will appear and feel considerably more diverse, inclusive, and accessible despite the obstacles. 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Biometric Security: The Future Of Cybersecurity

Cybersecurity is becoming a more significant issue in every aspect of our lives, with breaches and leaks happening regularly. With this in mind, it’s clear that there needs to be a better way to protect the private information we use on websites and apps daily. Biometrics offers an alternative to passwords and security questions, which are often easy for hackers to guess or access and challenging for many people to remember. In this article, you’ll learn how biometric technology works and its advantages over current authentication methods. What is Biometric Security? Biometric security is a term used to describe physical or behavioral characteristics to authenticate an individual’s identity. These authentication methods can be used alone or in combination with other security measures, such as passwords or PINs. One of the most common biometric authentication methods is fingerprint recognition. Fingerprints are unique to each individual and are challenging to duplicate. As such, they provide a substantial level of authentication for individuals seeking access to sensitive information or systems. Other biometric authentication methods include iris recognition, facial recognition, and voice recognition. These methods are often used in combination with one another to provide an even higher level of security. Biometric security systems are becoming increasingly common as the world moves towards a more digital society. They offer a high level of security that cannot be duplicated or bypassed, making them an ideal way to protect sensitive information and systems. How are Biometrics Used in the World Today? Biometrics are becoming increasingly popular for security and identification purposes. Here are some of the ways biometrics are used in the world today: 1. Access Control: Biometrics can control access to physical spaces like buildings, offices, and data centers. They can also control access to digital resources like computers, networks, and files. 2. User Authentication: Biometrics can be used to verify a user’s identity before allowing them to access sensitive information or perform specific actions. This is often used in combination with other forms of authentication, such as passwords or PIN numbers. 3. Transaction Security: Biometrics can be used to add an extra layer of security to financial transactions, whether they’re conducted online or in person. This helps prevent fraud and ensures that only authorized users can access accounts and make changes. 4. Law Enforcement: Biometrics are often used by law enforcement agencies for things like identifying criminals and tracking their movements. In some cases, biometric data can be collected from crime scenes and compared against databases of known offenders. 5. National Security: Government agencies sometimes use biometrics for national security purposes, such as screening people who enter the country or accessing classified information. How are Biometrics Used in Cybersecurity? Biometrics are already being used in a variety of ways to improve cybersecurity. One way is through the use of authentication, which can be used to verify the identity of a user before allowing them access to sensitive information or systems. This can be done through fingerprint, iris, or vein recognition devices. Another way biometrics are being used to improve cybersecurity is through behavioral analysis. This involves using algorithms to analyze a user’s behavior to detect anomalies that could indicate malicious activity. This information can then block access to resources or take other corrective action. As you can see, there are many different ways that biometrics are already being used to improve cybersecurity. Still, other uses for biometrics in cybersecurity include activity monitoring, data encryption, and fraud detection. And as technology continues to evolve, even more services will likely be found for this exciting new field. Pros and Cons of Biometric Security There are many benefits and disadvantages to using biometric security measures. Let’s check it out: Pros: 1. They are more secure than traditional methods like passwords or PINs. 2. They are less likely to be forgotten or lost. 3. They can’t be stolen or copied as passwords can. 4. They offer a higher level of convenience and usability. 5. They can be used with other security measures for added protection. Cons: 1. Biometric data can be stolen. 2. If biometric data is stolen, it can be used to spoof the system and gain access to sensitive information or areas. 3. Biometric data is not always accurate. For example, if a fingerprint sensor is not working properly, it may allow someone with a similar fingerprint to gain access. 4. Biometric systems can be expensive to implement and maintain.  5. They can be intrusive and invasive. For example, some people may not feel comfortable having their fingerprints taken, or their irises scanned. Future of Biometric Security The need for robust cybersecurity measures grows as the world becomes increasingly digitized. Biometric security is one of the most promising and effective ways to protect data and systems from unauthorized access. Biometric security systems use physical or behavioral characteristics to verify a person’s identity. Common examples include fingerprint scanners, iris scanners, and facial recognition technology. These systems often combine with other authentication methods, such as passwords or PIN numbers. Biometric security has several advantages over traditional security methods: * Biometric data is unique to each individual, making it more difficult for hackers to spoof or impersonate a legitimate user. * A password cannot be easily lost or forgotten in biometric data. * Biometric systems can be configured to require multiple-factor authentication, further increasing security. The use of biometric security is currently growing in both the consumer and enterprise markets. Smartphones, laptops, and other devices incorporate fingerprint scanners and biometric authentication forms. In the enterprise market, biometrics are used for everything from physical access control to logging into sensitive applications. The future of biometric security is bright. As the technology continues to evolve and become more sophisticated, we can expect to see even greater adoption in both the consumer and enterprise markets. Conclusion As the world becomes increasingly digitized, it’s essential to stay ahead of the curve regarding cybersecurity. Biometric security is one of the most promising new technologies in this field, and it will only become more prevalent in the future. It could very well be the key to keeping your data safe in the future. If you’re not already using biometric security measures, now is the time to investigate the available options. 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