In my latest contacts with clients, they keep coming up with an ontology. The question then arises: is this a new hype or a solid and essential concept for the future? The client's question proves the increasing interest in ontologies in recent years, due to the need for semantic clarity and data integration. It is not a new concept but has been a fundamental part of science for decades. The concept of ontologies emerged from a philosophy concerned with the nature of existence and the categorization of things. In the 1990s, ontologies were an important part of information, artificial intelligence, and semantics. It is not a new phenomenon, but the link with AI makes clear the revival of a proven and sustainable approach. With an increasingly complex and diverse data landscape, an Ontology provides a structured way to capture the tokens of data and define relationships between entities. Problems such as data silos, interoperability or semantic inconsistency are not temporary. If we coll

Over the past year, we’ve been hearing more and more about Apache Iceberg. But how can we explain what Apache Iceberg is to an information worker? The simple answer: “It’s like Excel, but for huge amounts of data.” We’re all familiar with the volume problem: an ever-growing number of Excel files stored in folders on our hard drive or in the cloud. Every day, we waste valuable time trying to: Find the right file Find the correct version Go back to a previous version Add an extra column Fix mistakes Without Iceberg, you rely on file names and folder structures to manage your data. With Iceberg, you get a smart system that: Keeps track of everything neatly Supports version control Helps you search quickly and accurately Where did Apache Iceberg come from? We all know Netflix, one of the largest data platforms in the world. They stored massive amounts of data in Amazon S3 using Apache Hive tables. But they ran into serious challenges when trying to provide a fast and reliable system for th