Metadata for BI and
Analytics Solutions


Executive Summary:

Whereas data is potential information, metadata is a statement about that potential information. There are several distinct categories of metadata that make different kinds of statements — descriptive, administrative, structural, markup languages, and use metadata — with numerous subcategories. A metadata schema, also known as an element set or data dictionary, provides a structured framework for metadata. Within the field of business intelligence (BI), metadata is essential for extracting, transforming, and loading data into a data warehouse, and for analyzing data once it’s there. In BI, metadata can be leveraged to support governance, risk management and compliance (GRC), launch automation, enable chargeback, facilitate upgrades and migrations, organize content for the purpose of monitoring, and provide insight into the adoption of BI tools. Most organizations benefit from third-party metadata services solutions, like 360Suite, that centralize and process metadata inputs and transform them into data for business. What distinguishes 360Suite from a data warehouse is that it extracts only relevant data — metadata related to BI — into a data mart, which provides authorized users with easy, fast, reliable, and secure access to metadata that answers their business intelligence questions. As the volume of data grows exponentially, it becomes increasingly difficult to discover and understand the potential in potential information. Metadata services represent a new source of information to which other services are able to connect. This, in turn, generates new metadata and creates a greater need for metadata on metadata — BI on BI — to make information available for machine learning, artificial intelligence, and business analytics.


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