If innovation is the ultimate goal in business and technology today, then consider generative AI (gen AI) the vehicle taking us there — and a strong data strategy, the fuel. Despite all its promise of productivity gains and new discoveries, gen AI alone can't do it all. The technology needs a "very ready" data foundation to feed on, something the vast majority of businesses today (78%) do not possess, according to a new report by MIT Technology Review Insights, in partnership with Snowflake.

Here’s an easy-to-understand and straight-to-the-point guide to take a screenshot in Selenium. Make sure that you have already installed a Selenium library. If you haven't, you can have a look at Selenium documentation to see how. All good? Let's get going!

Every device, transaction, and interaction in our digital world generates an endless stream of data. By 2025, the amount of global data is expected to reach a mind-boggling 180 zettabytes. So, how do we extract and make sense of this growing data? That’s exactly where generative AI proves its value. This blog explains generative AI applications for document extraction and how this technology helps cut through the noise and zero in on exactly what you need.

Throughout my career in enterprise technology, I've witnessed numerous transformations play out across the Asia-Pacific (APAC) region. But the shift we're seeing now with data streaming is truly unprecedented. What was once a supportive technology is rapidly becoming the very foundation of modern business in our region.

We are now in the final chapter of Apache Kafka’s multi-year journey to remove Apache ZooKeeper and fully transition to self-managed metadata in KRaft. Many Kafka users and customers are beginning to migrate to KRaft and are eager to understand its performance characteristics in production environments.