Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of large AI models, integration with graph databases is now required. This process ...

As enterprises continue to navigate the complexities of digital transformation, connected data is becoming an increasingly common necessity. Connected data is when data assets are linked together to ...

The development of database technology is one of the defining achievements of the information technology era. It not only has been the key to dramatically improved record-keeping and business process ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

A next-generation graph-relational database (DB) system has been developed in South Korea. If this system is applied in industrial settings, artificial intelligence (AI) will be able to perform ...

Every decade seems to have its database. During the 1990s, the relational database became the principal data environment, its ease of use and tabular arrangement making it a natural for the growing ...

Douglas Adams once wrote of a Holistic Detective Agency. The central character in this story, Dirk Gently, was able to solve cases with his understanding of the fundamental interconnectedness of ...

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it makes ...

Learn the key differences between relational and NoSQL databases with this in-depth comparison. There’s nothing wrong with the traditional relational database management system. In fact, many NoSQL ...