In an era where data is a strategic asset, organizations often falter not because they lack data—but because their architecture doesn’t scale with their needs.

The flexibility of data lakes, combined with the variety and vast amount of their stored data, makes them ideal for advanced analytics.

The Importance of Data Architecture With robust data architecture in place, everyone in your organization gets access to relevant data, based on which they can make informed decisions. Data ...

A data warehouse is defined as a central repository that allows enterprises to store and consolidate business data extracted from multiple source systems for the task of historical and trend ...

First, there was a data warehouse – an information storage architecture that allowed structured data to be archived for specific business intelligence purposes and reporting. The concept of the ...

The three-level DBMS architecture makes database design more secure, extensible and accessible for client applications. Learn the basics of how it works, with examples.

To gain business value from data, enterprises need to get their data architecture right – and the right business leadership and culture is critical to that.

The Future of Open: What's Next in Lakehouse Architecture As AI adoption continues to accelerate and the data demands of businesses grow ever larger and more complex, building a strong data foundation ...

TiDB is a prime example of an intrinsically scalable and reliable distributed SQL database architecture. Here’s how it works.

What exactly is a data architecture? As the Zachman Framework exposed long ago, different people look for different kinds of details and documentation to answer fundamental questions about an ...