TDAN
MAY 4, 2021
The expansion of big data applications has created opportunities across economic sectors. In healthcare, however, the potential of big data applications goes far beyond the financial. The contextual data gleaned from big data can drive healthcare solutions and accessibility to new heights.
Alation
FEBRUARY 28, 2023
For this reason, people often struggle to make vital business decisions as they face a complex data landscape. Metadata is the information about data that gives it meaning and context. It helps to answer basic, yet important questions like: “What does this data mean?”, “Which data is used the most?”
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IBM Big Data Hub
DECEMBER 16, 2022
An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.
erwin
AUGUST 6, 2020
It allows both IT and business users to discover the data available to them and understand what it means in common, standardized terms, and automates common data curation processes, such as name matching, categorization and association, to optimize governance of the data pipeline including preparation processes.
Alation
JUNE 28, 2022
This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.
AWS Big Data
APRIL 2, 2024
Data consumers need detailed descriptions of the business context of a data asset and documentation about its recommended use cases to quickly identify the relevant data for their intended use case. Data consumers have more contextualized data at their fingertips to inform their analysis.
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.
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