Ontotext

MAY 26, 2021

This happens through the process of semantic annotation , where documents are tagged with relevant concepts and enriched with metadata , i.e., references that link the content to concepts, described in a knowledge graph. Evaluation is for AI systems what quality assurance (QA) is for software systems.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

MAY 17, 2022

And today, it’s much harder to scale a person than a machine learning model. An enterprise data catalog is one such key asset. Those algorithms draw on metadata, or data about the data, that the catalog scrapes from source systems, along with behavioral metadata, which the catalog gathers based on human data usage.

Metadata 52

Metadata Data Quality Machine Learning Reporting 52

Octopai

DECEMBER 12, 2021

What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Without metadata, data is just a heap of numbers and letters collecting dust. Where does metadata come from?

Metadata 93

Metadata Management Data Quality Data Governance 93

erwin

DECEMBER 6, 2019

As a foundational component of enterprise data management, DG would reside in such a group. Enterprise Data Management Methodology : DG is foundational to enterprise data management. metadata management, enterprise data architecture, data quality management), DG will be a struggle.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

Alation

JANUARY 13, 2022

Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Data fabric has captured most of the limelight; it focuses on the technologies required to support metadata-driven use cases across hybrid and multi-cloud environments. The key is metadata.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52