But existing RPA customers faced the prospect of rewriting their RPA applications and management tools.“Migrating an entire digital workforce used to be incredibly expensive and time-consuming, so it was essentially a non-starter, even if there was significant interest in Microsoft’s offering,” Shimmerman said.Blueprint’s offering could dramatically lower this cost and set companies up for improved governance down the road.RPA versus low-codeBefore RPA came along, process efficiency experts developed a whole science around business process management systems.Process wonks would descend on a corporation and tease out how processes worked and how they could be re-engineered, then worked with business process management suites to convert these into executable business processes.An RPA bot is instantly understandable by any user, and it can work with any app at the user interface (UI) level, which provides significant flexibility.The development and evolution of Microsoft Power Automate took insight from both the RPA and low-code camps to provide the best of both worlds, with applications that could be created much like RPA bots but could run at the speed of low-code apps.Bringing process into RPA migrationsBoth RPA and low-code tools have traditionally focused on the technical side of automation.Additionally, most organizations rely on documents to specify their automations which may be missing or out of date.The new Blueprint Enterprise Automation Suite tool refactors RPA bots into a common object model.
May Allah grant you and your family peaceful and prosperous life.May this festival of sacrifice, faith, and purity abundant your life with joy and good health.Wishing you the heartiest Eid al-Adha Mubarak!
May this day be a symbol of joy, prosperity, and happiness in your lives.On this 4th of July let us salute all those brave men and women who fought for our country.Have a Happy Independence day.
Wishing you a very Happy Doctors Day!"Doctor’s Day is a reminder to all of us to take some time out to appreciate the doctors who put all their lives into offering services to others."You’re the true HERO of our universe!#DoctorsDay #DoctorsDay2021 #doctors #HappyDoctorsDay #HappyDoctorsDay2021 #NationalDoctorsDay #kairostech #kairos
With the ever-increasing number of big data applications in the world, the demand for big data testers is now more critical than ever.Hence, we have asked experts in the industry to share their knowledge on big data testing and its rising importance.What is big data testing?Big data testing is the process of testing data for data and processing integrity; and to validate the quality of big data and ensure data is flawless to help business derive the right insights, according to Hitesh Khodani, Test Transformation Manager.Marco Scalzo, Big Data Engineer at AgileLab, adds that when we talk about big data, we refer to a large collection of data, which is potentially unbounded if we are in a real-time streaming model, on which we execute a pipeline of operations in order to process data and store them in an external sink such as a database.For this reason, the traditional software testing techniques are not suitable for big data testing.A common approach to validate the correctness of data is to compare the source data with the ingested data.Another important test is the data processing test, which is very important as its primary focus is moved on the aggregated data.It’s easy to notice that the use of appropriate strategies of big data testing will reduce the time to market because it leads to testing the entire data processing pipeline of complex big data applications, monitor each step, easily scale and go into production in a fast way.Another important thing is that AI needs data to learn and evolve, and data requires AI-driven analytics to have the possibility to offer real value.The concept behind this is that like oil, raw data are not valuable by themselves, but the value is created when they are processed completely and accurately and this is done in a timely manner.Indeed, as Marco points out, big data analysis can improve the decision-making process or, even better, automate the whole decision-making process.It democratizes data and it is a cost-effective way to store all data of an organization and analyze them later.This current approach with a centrally managed data lake integrates all data sources, transforms data, and exposes them to all the consumers.It offers the possibility to empower agile and scalable analytics.The Data Mesh idea also increases the data scalability by moving towards a distributed-domain-oriented data platform and start to consider data as a product.
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Such include better quality testing and higher efficiency.Machine learning helps identify patterns for the prediction of future trends.AI in test automation; what is its role?Automation helps quality assurance (QA) specialists increase efficiency in processes.Advantages of using such technologies include:-The ability to handle repetitive tasks:Generation of relevant data for decision makingEarly detection and correction of bugs, amongst others.There is a need to continuously improve the functionality of the tools.AI can help with configuration and increase the reliability of the results.The capability of AI-generated unit tests depends on and mirrors the codes you build them on.AI can also cover larger test areas.It looks at operating systems, hardware requirements, and browsers.It then determines applicable UI standards while considering the end user’s needs.Increasing confidence levels with machine learning (ML)Establishing confidence levels is the process of estimating the performance of ML algorithms on unseen data.
In this article, we outline how can small QA teams make the transition from manual to codeless testing to full-fledged automated testing.For example, a script to import test data into a database, a utility to generate random test data, etc.2 – Know impediments to switch to automated testingOnce you acknowledge as a team that you need to move to automated testing, the next step is to know what is stopping your team from making this move.For example, think before picking a tool that does not work well with iFrames if your application is using iFrames heavily, or start to build out a test automation framework if your team doesn’t have any automation experience, etc.3 – Start simple and small but make it successfulA good beginning is half the job done.Don’t go crazy with automation and start with most time taking or complex ones first or you will make your beginning harder and reduce your chances of success.It will be easier when you choose combination of tools and frameworks.Codeless testing tools could cover most of your simple to medium complex manual tests.5 – Learn and practice programmingPick up the programming language that your team is most comfortable with.
Test automation avoids those issues by enabling test execution without any human interference.Speed and accuracy optimization: Test automation brings efficiency to the testing process—it shortens the time spent versus manual testing.Boosts reusability and upgrade capability: The testing solution and software is reusable and can be upgraded and kept up-to-date.Thus, even if the automation looks costly initially, the software is a long-lasting, reusable product.User environment simulation: Generally, automation testing is applied to simulate a typical user environment, making use of categorically employed keystrokes and mouse clicks.With such attributes, players in the global automation-testing market are quickly moving to introduce new services and solutions to the industry.To illustrate, Tricentis, which offers a testing platform for modern cloud and enterprise applications, announced in March 2021 its next-gen release of TestProject.It also focuses on the tedious test cases for healthcare applications, freeing testers to perform exploratory and regression testing.In the wake of COVID-19, more healthcare conglomerates are turning to automation testing and upgrading their existing solutions.Furthermore, the new facility will be implementing emergency-use-authorization approved PCR testing for COVID-19 tests, along with influenza A & B PCR testing.In short, the healthcare industry can’t function without proper healthcare applications, which is why it becomes important to be efficient, secure, and capable of handling large quantities of data.And the solutions must comply with the HIPAA and other regulations.
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Kairos Technologies Quality Engineering Center of Excellence (QECOE) is a ready framework, of our internal test organization, used to establish a value-based service for our enterprise customers.
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We combine the power of Data Science and Test History in your ALM and Test Management tools to produce more value from testing.
The power in our digital simulation framework comes from the test basis we create from a variety of sources.We respect all the data, be it historic bug reports, incidents, or the key metrics.We also consume (and produce) analytics from your existing mechanisms in crafting our library of Digital Test Patterns.
Women have the power to change the world if they put their heart and soul to shape the world with their eloquence, diligence, passion, and hard work.They will also need to have strong will power to be resilient and persevere to achieve their ambitions and goals.
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Even with the accelerating rollout of new digital tools and platforms, organizations don't often find success, or even fulfillment, when it comes to the digitalization of their businesses.According to 2018 Gartner research, nearly nine in 10 senior business leaders say their companies prioritize digitalization, yet two-thirds of transformations are unsuccessful.Data from McKinsey shows that only 16% of executives said their digital transformation initiatives were succeeding — due in large part to employee resistance and lack of managerial support.Over the years, the idea of transforming into a digital business has been massaged and stretched so much that it can be hard for organizations to fully imagine their digital destination.As the CMO of a company that offers business and technology transformation services, I believe that for organizations to take advantage of disruptive technologies like IoT, AI and robotics in the name of increasing profit or realizing new revenue streams, they must recognize that existing digital business approaches have been largely unproductive.PwC research suggests that while companies are making budget cuts, they're protecting digital transformation budgets ahead of other areas.If companies want to truly enable digital business with that spend, they should understand the nuances of digging deeper, changing in short spurts, and creating new opportunities from existing assets.Transformation requires practitioners, not just experts in new technologies.Enterprises often enlist the help of experts in particular technologies, software or language to guide their digital transformation decisions.These experts' knowledge is usually a mile deep and an inch wide — that is to say that their knowledge of their niche is bottomless, but their application experience within a particular industry might be rather narrow (or sometimes nonexistent).The model I've seen work time and time again for the largest global enterprises is focusing on collaborating, iterating and creating solutions with their digital teams and business partners.They should look for team members who can step back and comprehend the bigger picture, can understand the pain points of the customer and are well-positioned to solve them.Also Read : Digital Transformation ServicesTransformation is not a singular, big-bang event and doesn't have to be expensive (really).If someone were to tell me they were going to completely and radically change my business to accelerate growth and income, and it wasn't going to be expensive or take very long, I'd be skeptical.You should use a bite-sized, incremental approach to deliver results and greatly lower implementation risk.When business and IT leaders collaborate in short sprints, I've found that it creates faster and less costly results.
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