Content related to How Data Scientists Find Relevant Data with a Data Knowledge Graph
Out of many, one: Building a semantic layer to tear down knowledge silos
Guillermo Galdamez, Principal Consultant, and Nina Spoelker, Consultant, jointly delivered a presentation titled ‘Out of Many, One: Building a Semantic Layer to Tear Down Silos’ at the 2024 edition of LavaCon. Guillermo and Nina provided practical, proven guidance on how … Continue reading
Consolidation in the Semantic Software Industry
As a technology SME in the KM space, I am excited about the changes happening in the semantic software industry. Just two years ago, in my book, I provided a complete analysis of the leading providers of taxonomy and ontology … Continue reading
How Data Becomes Dark
Are you navigating through the complexities of managing your enterprise’s unstructured data? This infographic shows the journey from data creation to its eventual transformation into ‘dark data’—data that remains underutilized and potentially exposes organizations to risks. We break down the … Continue reading
A Semantic Layer Approach to Enterprise Knowledge Management and Information Findability
Within an organization or enterprise, multiple knowledge organization systems tend to be siloed and used for different purposes in different systems (the website, the intranet, technical documentation publishing, the product catalog, customer support articles, training materials, etc.). If this disparate … Continue reading
Mastering the Dark Data Challenge: Harnessing AI for Enhanced Data Governance and Quality
Enterprise Knowledge’s Maryam Nozari, Senior Data Scientist, and Urmi Majumder, Principal Data Architecture Consultant, presented a talk on “Mastering the Dark Data Challenge: Harnessing AI for Enhanced Data Governance and Quality” at the Data Governance & Information Quality Conference (DGIQ) … Continue reading
The Metadata Knowledge Graph
Modern data landscapes are characterized by immense volumes of diverse, disparate, and dynamic data sources, leaving many organizations struggling to effectively manage and derive value from their data assets. To address these challenges, a metadata knowledge graph serves as a … Continue reading
A Tale of Two Semantic Layers
In the rapidly evolving landscape of information and data management, the term Semantic Layer is increasingly utilized to describe two different types of ‘layers’ in the modern data stack. The first Semantic Layer is focused on enabling centralized analytics within … Continue reading
Building a Semantic Layer of your Data Platform
Enterprise Knowledge’s Joe Hilger, COO, and Sara Nash, Principal Consultant, presented “Building a Semantic Layer of your Data Platform” at Data Summit Workshop on May 7th, 2024 in Boston, Massachusetts. This presentation delved into the importance of the semantic layer … Continue reading
Analyzing and Optimizing Content for the Semantic Layer
As I wrote in my previous post, Adding Context to Content in the Semantic Layer, the organizational challenge of effectively generating, managing, and distributing content can be addressed by integrating content into a semantic layer. The semantic layer enriches the … Continue reading
Enterprise Knowledge Graphs: The Importance of Semantics
Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “Enterprise Knowledge Graphs: The Importance of Semantics” on May 9, 2024, at the annual Data Summit in Boston. In her presentation, Hedden describes the components of an enterprise knowledge graph and provides … Continue reading