IBM Big Data Hub

AUGUST 23, 2023

Because of this, when we look to manage and govern the deployment of AI models, we must first focus on governing the data that the AI models are trained on. This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. and watsonx.data.

Data Governance 56

Data Governance Enterprise Modeling Risk 56

IBM Big Data Hub

DECEMBER 16, 2022

With a data catalog, Alex can discover data assets she may have never found otherwise. An enterprise data catalog automates the process of contextualizing data assets by using: Business metadata to describe an asset’s content and purpose. A business glossary to explain the business terms used within a data asset.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Enterprise 79

Enterprise Data Integration Data Quality Contextual Data 79

erwin

JULY 17, 2019

In fact, data professionals spend 80 percent of their time looking for and preparing data and only 20 percent of their time on analysis, according to IDC. The solution is data intelligence. It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98