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The data ecosystem today is crowded with dazzling buzzwords, all fighting for investment dollars. A survey in 2021 found that a data company was being funded every 45 minutes. Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience.
The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledgegraph concept emerging as a pillar for data well and efficiently managed. And what are the commercial implications of semantic technologies for enterprise data? Source: tag.ontotext.com.
Seen through the three days of Ontotext’s KnowledgeGraph Forum (KGF) this year, complexity was not only empowering but key to the growth of knowledge and innovation. Content and data management solutions based on knowledgegraphs are becoming increasingly important across enterprises.
Cloudera Contributor: Mark Ramsey, PhD ~ Globally Recognized Chief Data Officer. July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. Luke: What is a modern data platform?
There’s been a lot of criticism that knowledgegraphs are too complex. So, why do we recommend knowledgegraphs, which are perceived to be complex, to our customers? Next, I will explain howknowledgegraphs help them to get a unified view to data derived from multiple sources and get richer insights in less time.
Datafabric is now on the minds of most data management leaders. In our previous blog, DataMesh vs. DataFabric: A Love Story , we defined datafabric and outlined its uses and motivations. The data catalog is a foundational layer of the datafabric.
Today, organizations are experiencing relentless data growth spurred by the digital acceleration of the past two years. While this period presents a great opportunity for data management, it has also created phenomenal complexity as businesses take on hybrid and multicloud environments. . How IBM built its own datafabric .
Datamesh is still in its infancy, and data personas and organizations are craving clarity and specificity. It is critical to be aware of the “why” and “what” and fully understand the role that knowledgegraphs play when considering adopting a datamesh strategy.
DataOps sprung up to connect data sources to data consumers. Architectures became fabrics. The data warehouse and analytical data stores moved to the cloud and disaggregated into the datamesh. Datafabric, datamesh, modern data stack. Tools became stacks.
Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that. What is data democratization?
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