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.

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.

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 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.

Learn to a knowledge base with an AI chatbot frontend to your BigQuery or unstructured Cloud Storage data using RAG and BigQuery ML.

Minimum Viable Architecture plays a critical role in the success of your MVP. Learn how to avoid the most common pitfalls in implementing this strategic approach.

Snowflake is a modern, robust data platform for cloud data management that provides users with the opportunity for unique scalability, flexibility, and performance. However, keeping costs under control is crucial to maximize the benefits on offer with this platform.

Software testing evolved from a simple debugging activity in the 1950s to becoming integral to software development with advanced testing tools and test estimation techniques. As a C-level executive or business developer, ensuring your teams provide accurate QA effort estimates is crucial. This precision influences the project outcome and bolsters your credibility with clients. Underestimating QA efforts can lead to potential underperformance and unclear requirements.

If you're noticing bottlenecks or disadvantageous data silos in your enterprise workflows, enterprise automation could be the answer.