Ontotext

FEBRUARY 19, 2020

As a result, a knowledge graph crafted with a view to a specific context and business data needs immensely broadens the opportunities this technology opens for smart data management. Here is our list of how to build a knowledge graph: Clarify your business/data requirements.

Modeling 90

Modeling Knowledge Discovery Data Quality Visualization 90

Ontotext

SEPTEMBER 15, 2020

It must not attempt to force or predict how the data is to be used but to enable that decision to be made by today’s user (and tomorrow’s) while still maintaining organization appropriate access control and security. Consider using data catalogs for this purpose. Clean data to ensure data quality.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Several factors are driving the adoption of knowledge graphs. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

AUGUST 31, 2023

The growth of large language models drives a need for trusted information and capturing machine-interpretable knowledge, requiring businesses to recognize the difference between a semantic knowledge graph and one that isn’t—if they want to leverage emerging AI technologies and maintain a competitive edge.

Modeling 64

Modeling Optimization Knowledge Discovery Enterprise 64