Websites and apps are slowly starting to integrate more collaborative features as a means of increasing interactivity and the functionality of various use-cases. Be it a collaborative document or a chat room, one common feature is to show who else is in the space with you. Typically this’ll be done with an Avatar Stack, a collection of icons, each representing a client connected to the space.

Looking to take the load off your data engineers and IT pros? And help business users create and analyze datasets on their own? You’re in the right place. In this article, we’ll review the best self-service analytics solutions on the market today: We'll look at the main features of each tool, its pros and cons, its best use cases, and user reviews to help you make the right choice. Before we delve into each one, let’s set the tone of what to expect from a good service analytics tool.

However, the entire change in the development practices has only been triggered considering the extensive need for improving or meeting the end user’s perspective. And the process involves the best of Agile, DevOps testing services, QAOPs, and DevSecOps practices. Talking specifically for DevOps, it not only streamlines development and operations, but helps foster collaboration through enhanced software delivery for added efficiency, quality, and access to automation.

Appian 23.4 is here! As usual, this release is full of new and enhanced capabilities that speed up development and make your work easier. Read on for the highlights, and watch the 23.4 Product Announcement webinar or read the release notes for more on what’s new in this release.

Have you heard this quote from Edwards Deming? – “In God we trust, all others bring data.” In today’s competitive landscape, if you’re not measuring your performance and closely analyzing each relevant data point, you’re not going to see much success with your strategies. This is the golden rule no matter what type of business you run – whether you’re a small, local jewelry store or Coca-Cola. And KPIs (key performance indicators) help us do just that.

Exit criteria in software testing are a set of predefined conditions or requirements that must be met before a software testing phase or software testing project can be considered complete and the software can move on to the next stage of development or release.

Data democratization can feel like just another business buzzword. But beyond the buzz, it represents an important concept: when your employees lack access to the data they need for decision-making, decisions will stall and your business will suffer. Getting value from your data—and delivering that across your organization—is a persistent challenge. Getting value from your data—and delivering that across your organization—is a persistent challenge.

Two names that have been making waves with their distinct approaches to building web apps are Next.js and Vite.js. Next.js is a React framework specialized in server-side rendering (SSR), static site generation (SSG), and hybrid applications. It provides features like file-based routing, image optimization, and is particularly suited for projects where SEO and fast initial load times are priorities.

Data is the cornerstone of your business. Appian 23.4 builds on this foundation with our AI, data fabric, and process automation capabilities—making it even easier to get value from your enterprise data. With the new self-service analytics capability, your business users can now securely access your data fabric to browse data catalogs, build reports, and chat with Appian AI Copilot to ask questions about their data.

Working as a software tester, are you sometimes tired of the repetitive and time-consuming nature of the whole process? If yes, a data-driven framework is exactly what you need. A data-driven framework in Selenium is an approach to automated testing that separates test scripts from test data, enabling testers to run the same test script with different data inputs.