Systems | Development | Analytics | API | Testing

BigQuery has three new categories of advanced aggregation functions: group by extensions, user-defined and approximate aggregate functions.

BigQuery ML TimesFM model is now in preview, and forecasts datasets through the use of generative AI.

A few years ago, if you asked someone to define “vibe data engineering,” you’d probably get a puzzled look. Today, it's a phrase that's beginning to surface in conversations across enterprise teams, especially among those who need data to work for them, not the other way around. It doesn’t mean writing the cleanest DAGs or orchestrating distributed clusters. It means making data work fluidly, simply, and on your terms. It means doing more with less, and doing it without code.

Automated testing is essential for providing quality software in today's high-velocity development environments. So, Microsoft developed Playwright, an open-source framework for automating user interactions with web browsers. It is used for end-to-end testing of web applications. Playwright, Microsoft’s advanced end-to-end testing framework, has gained popularity among developers and QA teams because of its cross-browser capabilities and feature set.

At Qlik, we’re incredibly proud of our Luminary and Partner Ambassador communities. They’re more than customers, more than partners, they’re an integral part of who we are. For over a decade, hundreds of data leaders across industries and continents have proudly called themselves Qlik Luminaries and Partner Ambassadors. With new people joining every year, this global network keeps growing, but one thing never changes: these folks bring the spark.

Quality assurance (QA) is no longer an optional luxury in today’s software development, it is a necessity. As applications become more complex, executing or managing hundreds or thousands of tests by hand is increasingly impractical. Testing suites in software testing provides a way to manage a formal collection of test cases to test various aspects of a software application systematically.

In today’s data-driven world, collecting data is easy, but making sense of it is what truly matters. That’s where Pandas pivot tables come into play. With just a few lines of Python, you can quickly turn disorganized data into meaningful, well-structured summaries. Imagine Excel pivot tables, but faster, more flexible, and fully powered by code.

AI systems need both structured data (like spreadsheets) and unstructured data (like images or text). SQL databases excel at structured data, while vector databases handle unstructured data for tasks like similarity searches. The solution? Hybrid AI stacks that combine both through unified Data AI Gateways.