Contrary to popular belief, the most meaningful developments in contemporary data architecture aren't the rising interest in the concepts of the data mesh or the data fabric. It’s actually the merging ...

AI—both operational and generative—is knocking on enterprises’ doors, forcing data managers to make new architectural choices on what it will take to support these data-hungry initiatives. Data mesh ...

Legacy architecture and monolithic data platforms can pose significant challenges to effectively scaling data and analytics. While data sources, domains, and consumers all continue to proliferate and ...

Modern businesses generate vast amounts of data, which is ultimately distributed across various cloud databases, local apps, on-prem servers, and the edge. Disconnected, disorganized and siloed data ...

Data fabric is a powerful architectural approach for integrating and managing data across diverse sources and platforms. As enterprises navigate increasingly complex data environments, the need for ...

The data fabric has emerged as an enterprise data management pattern for companies that struggle to provide large teams of users with access to well-managed, integrated, and secured data. Now ...

Understanding the differences between data mesh, data fabric, and data virtualization can help organizations turn scattered data into a strategic advantage.

Throughout my career, enterprise data management paradigms have come and gone. Let’s briefly trawl some data management history to understand how data fabric emerged. Okay, “data swamp” is somewhat ...

As 2022 beckons, the big data ecosystem finds itself in a transitional state of flux that may very well redefine everything you know—or thought you knew—about it. The cloud is still its unambiguous ...

Throughout my career, enterprise data management paradigms have come and gone. Let’s briefly trawl some data management history to understand how data fabric emerged. Okay, “data swamp” is somewhat ...