Software testing that confirms if a system or application satisfies the necessary specifications and business needs is called acceptance testing. It is usually performed at the end of the software development life cycle, after unit testing and integration testing have been completed. The main goal of acceptance testing are to : Instead of the development team, end users, business stakeholders, or customers frequently conduct acceptance testing.

Data elements are the fundamental building blocks of EDI documents. They represent individual information within a transaction set, such as city, state, country, item number, quantity, and price. Each data element is defined by its data type, which specifies whether it’s numeric, alphanumeric, a date, or a time. Additionally, the definition includes details like minimum and maximum length requirements and any applicable code values.

If you’re a developer or QA person, you know the importance of running different performance tests to determine how changes in code could affect performance. This highlights the importance of performance testing in the software development lifecycle. Performance testing measures a system’s overall performance under various conditions, load testing measures its performance under expected user loads, and stress testing evaluates its behavior under extreme conditions to identify breaking points.

What is data fabric architecture? The case for data fabric 4 key facts about data fabric architecture Data fabric architecture can modernize and future-proof your data approach Data fabric architecture is a virtual data layer that connects any number of external systems together to provide unified access and a complete, 360-degree view of an organization’s data. Whether your data lives in legacy systems or multi-cloud environments, a data fabric can connect these systems together for a unified view.

Mobile apps are the key to business success, accounting for a quarter of companies’ revenue, according to Kobiton research. However, 75% of companies report that slow app releases cost them over $100,000 annually, making efficient and timely app testing essential. These statistics call for complete native app testing, which involves testing apps built specifically for a certain operating system.

Web applications have become the backbone of businesses—from eCommerce platforms like Amazon to social networks like Facebook. Unlike traditional websites that simply present information, web apps let users interact, make transactions, or even collaborate in real-time. Whether you're a small startup looking to streamline operations or a large enterprise needing scalable solutions, web apps make it all happen. But how do you go from idea to execution?

I shouldn’t have to convince anyone that Apache Kafka is an incredibly useful and powerful technology. As a distributed event streaming platform, it’s adept at storing your event data and serving it up for downstream consuming applications to make sense of that information––in real time or as close to real time as your use case permits. The real beauty of Kafka as a technology is that it can do it with very little effort on your part. In effect, it’s a black box.

In just 12 short months, the Connect with Confluent (CwC) technology partner program has transformed from a new, ambitious initiative to expand the data streaming ecosystem into a thriving portfolio that’s rapidly increasing the breadth and value of real-time data. The program now provides a portfolio of 50+ integrations, each one amplifying the capabilities of Confluent's unified data streaming platform for Apache Kafka and Apache Flink.

According to recent research, scaling intelligent automation could save the Energy & Utilities industry between $237 billion and $813 billion in operational costs. Despite this immense potential, utility providers still grapple with intense competition, increasingly stringent regulations, and aging infrastructure and workforce challenges. The demand for more affordable and cleaner renewable energy only adds to these pressures.