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This content is part of the comprehensive Governance in Tableau documentation.

Metadata management includes policies and processes that ensure information can be accessed, shared, analyzed and maintained across the organization, as an extension of Data Source Management. Metadata is a business-friendly representation of data in common terms, similar to a semantic layer in traditional BI platforms. Curated data sources hide the complexity of your organization’s modern data architecture and make fields immediately understandable regardless of the data store and table from which it was sourced.

Key Considerations

Implementation Details

Tableau employs a simple, elegant, and powerful metadata system that gives users flexibility while allowing for enterprise metadata management. The Tableau Data Model can be embedded in a workbook or centrally managed as a Published Data Source with Data Server. After connecting to data and creating the Tableau Data Model, which will become a Published Data Source on Tableau Server or Tableau Online, look at it from your users’ perspective and see how much easier analytics will be when they have a well-formatted starting point, filtered and sized to the business questions it can answer. For more information on Published Data Sources, visit The Tableau Data Model, Best Practices for Published Data Sources and Enabling Governed Data Access with Tableau Data Server.

The diagram below shows where elements exist in the Tableau Data Model:

Data Model Diagram

Beginning in 2020.2, the Data Source includes the connection, connection attributes, and the physical and logical layers within a Data Model. Upon connection, Tableau automatically characterizes fields as dimensions or measures. In addition, the Data Model stores calculations, aliases, and formatting. The physical layer includes physical tables defined by joins, unions, and/or custom SQL. Each group of one or more physical tables defines a logical table, which resides in the logical layer along with relationships.

Relationships are a new way to model data that is more flexible than using joins. A relationship describes how two tables relate to each other, based on common fields, but it does not combine the tables together as the result of a join does. Relationships provide several advantages over using joins.

At run-time in the VizQL model, multiple queries are built dynamically based on the dimensions and measures of the visualization and filters, aggregations, and table calculations are applied. Tableau uses the contextual information of the separate logical table to determine what joins are applied to provide the correct aggregation. This enables one user to design the Data Source without needing to know, plan, or otherwise account for all the variations of analysis to be performed with the Data Source by other users. Tableau Catalog discovers and indexes all of the content on Tableau, including workbooks, data sources, sheets, and flows.

Data stewards or authors with direct access to sources of data should prototype data sources as an embedded data source in a Tableau workbook and then create a Published Data Source in Tableau to share the curated Tableau Data Model, as shown below in the direct access workflow:

Direct Access Workflows

If authors do not have direct access to sources of data, they will rely on a DBA or data steward to provide the prototype data source embedded in a Tableau workbook. After reviewing and verifying it contains the needed data, a Site Administrator or Project Leader will create a Published Data Source in Tableau to share the Tableau Data Model, as shown below in the restricted access workflow:

restricted access workflows

The metadata checklist identifies best practices for curating a Published Data Source. By establishing data standards using the checklist, you’ll enable the business with governed self-service data access that is user-friendly and easy to understand. Prior to creating an extract or Published Data Source in Tableau, review and apply the following checklist to the Tableau Data Model:

Beginning in 2019.3 in the Data Management Add-on,Tableau Catalog discovers and indexes all of the content on Tableau, including workbooks, data sources, sheets, and flows. Indexing is used to gather information about the metadata, schemas, and lineage of the content. Then from the metadata, Tableau Catalog identifies all of the databases, files, and tables used by the content on your Tableau Server or Tableau Online site. Knowing where your data comes from is key to trusting the data, and knowing who else uses it means you can analyze the impact of changes data in your environment. The lineage feature in Tableau Catalog indexes both internal and external content. For more information, see Use Lineage for Impact Analysis.

lineage impact analysis in Tableau

lineage graph

Using lineage, you can trace down to content owners at the end of the lineage graph. The list of owners includes anyone assigned as the owner of a workbook, data source, or flow, and anyone assigned as the contact for a database or table in the lineage. If a change is going to be made, you can email owners to let them know about its impact. For more information, see Use email to contact owners.

Learn More

For additional detail, review the Tableau Blueprint and information included in Tableau Governance.