Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). granules) of the data collection for fast search, access, and retrieval is also important for efficient orchestration and delivery of the data that fuels AI, automation, and machine learning operations. Collect, curate, and catalog (i.e.,

Strategy 266

Strategy Machine Learning Metadata Knowledge Discovery 266

Ontotext

AUGUST 22, 2023

Context: The Key to Making Data Useful It goes without saying that data without meaning can yield incorrect insights, leading to potentially dangerous decisions. Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

Ontotext

DECEMBER 1, 2023

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

Metadata 78

Metadata Sales Consulting Enterprise 78

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. Knowledge Graphs are the Warp and Weft of a Data Fabric.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

MARCH 8, 2023

Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. Graph-based solutions further leverage the relationships among the entities involved to create a semantically enhanced machine learning model.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

JULY 29, 2021

The Semantic Web started in the late 90’s as a fascinating vision for a web of data, which is easy to interpret by both humans and machines. One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. Take this restaurant, for example.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124