Systems | Development | Analytics | API | Testing

Database testing is the process of evaluating the accuracy, reliability, and performance of a database system. Its purpose is to ensure that the data stored there is consistent, valid, and can be correctly manipulated for business needs. The components to be tested are usually database schema, tables, and database triggers. Testers leverage SQL queries, data comparison tools, automation frameworks, or load testing tools to examine the data integrity, validity, security, performance, and structure.

There is no doubt about it: Artificial Intelligence (AI) and Machine Learning (ML) has changed the way we think about software testing. Ever since the introduction of the disruptive AI-powered language model ChatGPT, a wide range of AI-augmented technologies have also emerged, and the benefits they brought surely can’t be ignored. In this article, we will guide you to leverage AI/ML in software testing to bring your QA game to the next level.

We’ve got something truly special in store for you. We reached out to our expansive testing community, consisting of 40,000 testers, and posed a question about leveraging GPT prompts for various software testing scenarios and tips for effective prompting. The response was nothing short of astounding, and today, we’re thrilled to bring you the incredible insights we gathered. Prepare to be amazed as we unveil 15+ best ChatGPT prompts for software testing enthusiasts like you.

In the world of software-as-a-service, product-led growth (PLG) is an easy way to enable users to experience the value of a product firsthand, without restrictions. PLG can drive adoption, retention, and sustainable business growth with its robust and open framework. But what drives PLG best, a freemium model or a free trial? With freemium, your top of funnel growth can skyrocket, while free trials see a 2-3x higher conversion rate thanks to urgency (ie, users lose access immediately on trial end).

Companies want to train and use large language models (LLMs) with their own proprietary data. Open source generative models such as Meta’s Llama 2 are pivotal in making that possible. The next hurdle is finding a platform to harness the power of LLMs. Snowflake lets you apply near-magical generative AI transformations to your data all in Python, with the protection of its out-of-the-box governance and security features.

If Google Analytics isn’t configured properly across multiple websites, your performance data could be skewed. Here are 12 ways to properly set up and use Google Analytics across multiple websites.

What’s the difference between KPIs and metrics? How can you leverage both to improve your company’s performance?

Want to make 404 error reporting easier? This guide will help you understand what 404 errors are, how to track them, and what to do when they appear.

Ready, set…report! Learn how to write a thoughtful and well-structured business analysis report with this easy-to-follow guide.

If you’re interested in automating the testing of your web application, there are three categories of tools to understand: The best automated testing solution for your web application will depend largely on the resources you have and the tradeoffs you’re willing to make. In this piece, I’m going to help you understand the strengths and shortcomings that come with each of these types of testing tools, as well as who they’re each best-suited for.