ITSS 4356 Metadata Management​ Ch12​

Metadata

information about data’s structure and meaning​

Without reliable metadata

companies do not know what data they have, what it represents, where it originates from, who should access it, or its quality.

(Business Driver) Reliable metadata helps:

• Increase confidence in data by providing context and enabling the measurement of quality​
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• Increase value of strategic information by enabling multiple uses​
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• Improve operational efficiency by identifying redundant data and processes​
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• Prevent use of out of date or incorrect data​
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• Reduce data search time​
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• Improve communication between IT employees and data consumers​
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• Create accurate impact analysis to reduce risk of project failure ​
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• Improve time to market by reducing systems development lifecycle​
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• Support regulatory compliance

Metadata management focuses on:

Documenting and managing organizational knowledge of data related business terminology in order to ensure people understand data content and can use data consistently ​
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Metadata management also focuses on:​
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Collect and integrate metadata from diverse sources to ensure people understand similarities and differences between data from different parts of the company​

Business metadata​

• Naming and definitions of concepts, subject areas, entities, attributes, calculations, rules, etc.

Technical metadata​

• Technical details of data, systems, and processes that move data around​

• Physical columns, ETL, recovery and backup rules, primary keys, etc.

Operational metadata​

• Describes details of processing and accessing data​

• Error logs, batch programs, reports, archiving

Business metadata requires

stewards with good writing and facilitation skills to develop enterprise definitions of data in a business glossary.

Data Mapping

The process of establishing traceability between data pieces.

-Understanding how business terms map to their possible database locations is critical. ​

Business Intelligence, Big Data and Metadata

• The first step in analyzing data is easily obtaining reliable data that is permitted for use.​

Data Lineage

similar to a data lifecycle that includes data’s origin, destination, and changes.

Metadata for Big Data Ingestion​

Without metadata to provide context, a data lake quickly becomes a data swamp, which is why tagging data is a common practice to add meaning to the data being ingested.

Metadata Implementation Guidelines ​

• Follow an incremental, prioritized approach to minimize risk and business disruption.​

• Metadata readiness assessment​

• Organizational and cultural change​

• Common metadata gathering and managing ​

• Utilize metrics

Metadata Governance

Define standards and manage changes to metadata, while utilizing a workflow tool to document and track the progression of these changes.

Metrics can be used to determine the effectiveness or impact of lack of metadata:​

• metadata repository completeness​

• Steward representation​

• Metadata usage ​

• Metadata quality