Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). Labeling, indexing, ease of discovery, and ease of access are essential if end-users are to find and benefit from the collection. My favorite approach to TAM creation and to modern data management in general is AI and machine learning (ML).

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Machine Learning Consulting 78

Ontotext

MARCH 8, 2023

Several factors are driving the adoption of knowledge graphs. Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Ontotext

NOVEMBER 11, 2024

Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. As a hub for data, metadata, and content, they provide a unified, consistent, and unambiguous view of data scattered across different systems.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52