The way that companies govern data has evolved over the years. Previously, data governance processes focused on rigid procedures and strict controls over data assets. But now, with the data-driven culture, modern enterprises are adopting an agile approach toward data governance that primarily centers around data accessibility and empowering business users to take responsibility for governing and managing data.

Discover the new Artifact Details page and Private Install page from Bitrise, offering detailed artifact information that's easy to find, and secure to share.

The mid-sized enterprise is the fastest-growing market opportunity for data storage. But not just any storage system will do. These days, mid-sized enterprises must handle the complexities of unremitting data growth and distributed infrastructure, meet sustainability goals, manage the diverse storage needs of mission-critical applications, and respond to user requirements. Oh, and they need uninterrupted access to their data no matter what.

Automated data governance is a relatively new concept that is fundamentally altering data governance practices. Traditionally, organizations have relied on manual processes to ensure effective data governance. This approach has given governance a reputation as a restrictive discipline. But, as organizations increasingly adopt automation in their governance processes, this perception is changing.

As the wave of AI sweeps through the technology landscape, many have hopped on board. Interestingly enough, and often overlooked, is that many AI capabilities are served through APIs. Fancy user interfaces integrate with the actual mechanisms where the magic happens: the APIs. So, when generating revenue through AI platforms, the APIs drive the revenue.

Using BigQuery DataFrames with CARTO visualization tools can help Python users access cloud-native analytics and generative AI services.

When we initially started building our test recorder, we needed a way to validate the id attributes being used on the page. We would sometimes capture an id attribute in a recording, only to find that it failed when we used it in a test, because it didn’t meet specification. For instance, sometimes websites would use an id with a number in front, like this: That is technically invalid, at least in the HTML4 specification.