Ontotext

MARCH 13, 2024

Eventually, this led to the transformation of the project into forming an expansive knowledge graph containing all the marketing knowledge we’ve generated, ultimately benefiting the whole organization. OTKG models information about Ontotext, combined with content produced by different teams inside the organization.

Marketing 72

Marketing Knowledge Discovery Metadata Data-driven 72

IBM Big Data Hub

APRIL 15, 2024

For example, as manufacturers, we create a knowledge base, but no one can find anything without spending hours searching and browsing through the contents. Or we create a data lake, which quickly degenerates to a data swamp. Contextual data understanding Data systems often cause major problems in manufacturing firms.

Manufacturing 101

Manufacturing Contextual Data Knowledge Discovery Data Lake 101

Rocket-Powered Data Science

JULY 6, 2021

Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. So, there must be a strategy regarding who, what, when, where, why, and how is the organization’s content to be indexed, stored, accessed, delivered, used, and documented.

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

Ontotext

APRIL 6, 2023

Knowledge graphs are changing the game A knowledge graph is a data model that uses semantics to represent real-world entities and the relationships between them. It can apply automated reasoning to extract further knowledge and make new connections between different pieces of data.

Manufacturing 83

Manufacturing Cost-Benefit Knowledge Discovery Optimization 83

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. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

OCTOBER 28, 2021

It demonstrates how GraphDB and metaphactory work together and how you can employ the platform’s intuitive and out-of-the-box search, visualization and authoring components to empower end users to consume data from your knowledge graph. Data normalization is an essential step in the data preparation process.

Visualization 52

Visualization Interactive Knowledge Discovery Dashboards 52

Domino Data Lab

JUNE 15, 2021

Over the next decade, the companies that will beat competitors will be “model-driven” businesses. These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69