Enriching Technical Metadata

Use Data Catalog to enrich the harvested technical metadata.

Data Catalog lets you collect technical and business information of data assets in an organization so that all data users get a complete view of the data. Technical information is collected when you harvest the data sources. Business context is provided by data experts in the form of metadata enrichments to supplement the technical information.

Technical metadata includes details about the data source, such as table name, column name, and datatype. As a data consumer, these details may not provide you enough information to understand the data and use it. To determine if a data source is the right data for you, you also need to understand the business aspect of the data. For example, what is the data about, it’s intended usage, who owns this data, how often is the data updated; and in general, the tribal knowledge about the data.

Data providers or subject matter experts can use metadata enrichment capabilities in the data catalog to capture and share this type of information with others in the organization.

You can enrich technical metadata with business context in Data Catalog using the following options:

  • User-defined tags: For example, data providers can tag a table as Legacy to let the data consumers know they should be using the table with caution because it may contain old data.
  • Linked business glossary terms: For example, link a business term, such as Discount Code, to a column in a table to explain the business concept that column represents.
  • Custom metadata properties: For example, create link custom properties, such as Intended Usage, Data Owners, Update Frequency, and populate the custom properties with the right values.

Benefits of Enriching Technical Metadata

Enriching technical metadata has the following benefits:

  • Data consumers use the enrichment values for searching, filtering, and understanding the data without guessing or asking data providers. Metadata enrichment increases the ability of data consumers to quickly discover most appropriate data for their analytics and reduces their dependency on data providers or tribal knowledge in the organization.
  • Data providers get an effective way to share business context with the consumers and they don’t have to spend time answering the same questions again and again.