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Oracle has announced the launch of Oracle Fusion Cloud Sustainability — an app that integrates data from Oracle Fusion Cloud ERP and Oracle Fusion Cloud SCM , enabling analysis and reporting within Oracle Fusion Cloud Enterprise Performance Management (EPM) and Oracle Fusion Data Intelligence.
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.
Amazon DataZone enables you to discover, access, share, and govern data at scale across organizational boundaries, reducing the undifferentiated heavy lifting of making data and analytics tools accessible to everyone in the organization. Data consumers have more contextualizeddata at their fingertips to inform their analysis.
Data Literacy Definition. Gartner defines data literacy as the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied — and the ability to describe the use case, application and resulting value.
To achieve what the company would need going forward, McCowan knew Regeneron would have to undergo a major transformation and build a more enhanced data pipeline that could inject data from up to 1,000 data sources in “analytical ready formats” for both the business and the scientists to consume, the CIO says.
It also adds flexibility in accommodating new kinds of data, including metadata about existing data points that lets users infer new relationships and other facts about the data in the graph. Schemas are an example of how the right metadata can add value to the data it describes.
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?”
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.
Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextualdata 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.
Your organization won’t be able to take complete advantage of analytics tools to become data-driven unless you establish a foundation for agile and complete data management. You need automated data mapping and cataloging through the integration lifecycle process, inclusive of data at rest and data in motion.
It’s a truism that data is the most important asset in the 21 st century economy. But, today too many enterprises exist in a data fog, with poorly contextualizeddata scattered across millions of tables. Dispelling this data fog is one of the key challenges for the next generation enterprise.
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