Content related to What is a Large Language Model (LLM)?
The Value of Data Catalogs for Data Scientists
Introduction After the Harvard Business Review called Data Scientist the sexiest job of the 21st century in 2012, much attention went into the interdisciplinary field of data science. Students and professionals were curious to know more about what data scientists … Continue reading
Why Invest in a Knowledge Graph? Your Digital Transformation and Enterprise AI Initiatives Depend on It
The scope and success for digital transformations and advanced enterprise solutions is driven by a few factors, namely, defined use cases, available data, and people and SMEs. For many organizations, the biggest hurdle is knowing where to start. Starting with … Continue reading
Better Practices for Collaborative Knowledge Graph Modeling
As the scale and scope of the modern data ecosystem grows, we at EK see an increasing number of enterprises recognizing the potential for ontologies to make their data findable and usable throughout the organization. An ontology can provide robust … Continue reading
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid Knowledge Graph Implementation
Sara Nash and Thomas Mitrevski, Consultants in Enterprise Knowedge’s Data and Information Management Division presented on May 4, 2022 at the Knowledge Graph Conference in New York City. The talk focused on How to Quickly Prototype a Scalable Graph Architecture: … Continue reading
Digital Twins and Knowledge Graphs
Enterprise knowledge graphs are one of the fastest growing trends in knowledge management. Their intuitive and flexible structure, combined with their emphasis on relationships between entities, make knowledge graphs a natural fit for use cases that require aggregating content from … Continue reading
Where Does a Knowledge Graph Fit Within the Enterprise?
Our clients often assume that building a knowledge graph requires that all data be managed in a single place for it to be effective. That is not the case. There are a variety of ways that organizations can solve for … Continue reading
Translating AI from Concept to Reality: Five Keys to Implementing AI for Knowledge, Content, and Data
Lulit Tesfaye, a Partner and Director for Enterprise Knowledge’s Data and Information Management Division, presented on April 07, 2022 at the data.world Spring Virtual Summit 2022 on the topic of Translating AI from Concept to Reality: Five Keys to Implementing … Continue reading
A Data Scientist Perspective on Knowledge Graphs (Part 1): the Data-Driven Challenge
Photographer: Johannes Plenio This series of articles is a data scientist, and data engineer, perspective on knowledge graphs, which is intended not only for other data scientists and engineers, the nerdy role in the office that no one truly understands; … Continue reading
N-CATT – Data Strategy, Data Management and Data Governance Workshop
The Challenge National Center for Applied Transit Technology (N-CATT), a technical assistance center funded by the Federal Transit Administration and operated by the Community Transportation Association of America, seeks to provide small-urban, rural, and tribal transit agencies with practical, replicable … Continue reading
Transforming Tabular Data into Personalized, Componentized Content using Knowledge Graphs in Python
My colleagues Joe Hilger and Neil Quinn recently wrote blogs highlighting the benefits of leveraging a knowledge graph in tandem with a componentized content management system (CCMS) to curate personalized content for users. Hilger set the stage explaining the business … Continue reading