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Sharing Connections, Data Models, Data Extracts in Tableau

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Sharing connections, data models, and data extracts

Tableau’s data server can lower the data access barrier while still providing data governance control. Database administrators can define data connections once, publish them to the data server, and manage access by applying tableau’s object level. Consequently, data analysts using tableau require no knowledge of the underlying tables, joins, or related criteria driving the connections.

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Offering a common data library

It’s common for organizations to manage and use a variety of data sources. Transaction data may live in one database while historical data is maintained in another completely different database. Business users may maintain their own spreadsheets of forecasts and budgets. While tableau can easily connect to each of these disparate data sources, the data server offers the capability to host these connections in a central place. This reduces the potential for data misuse because tableau users can simply connect to the tableau server and the data they need access to, regardless of the source system. Data server simply acts as a proxy to databases at the same time serving as a host of items such as excel and access files, or even data extracts.

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Real-time example:

Brooklyn Public Library wanted to make faster, more data-driven decisions. But its reliance on outside consultants and a dated reporting solution made that impossible. After choosing Tableau Desktop and Tableau Server, the library is enjoying benefits such as:

  • Replaced 5 consultant roles with 1 new hire and 1 transitioned analyst
  • Cutting reporting time by 2 weeks
  • Eliminate financial reconciliation issues in the patron fine accounting system
  • Provide clear, easy to use reports on metrics to staff system-wide

After discovering Tableau, the team realized they could do far more than replace existing reports—they could speed decisions, improve insight, and tell their stories to management and to their public in a visual, exciting way.

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Sharing data models

Earlier in the post in the section related to the tableau data server, you learned how data sources can be published and used by many different users. The related metadata that comes with the shared data sources allows  data administrators to manage inconsistencies through:

  • Consistent field name aliasing
  • Consistent field grouping
  • Consistent application of field hierarchies

This permits the organization to tap into the best subject matter experts to create and validate calculations and also to publish the resulting data models for your entire organization to benefit from. These capabilities can reduce variations in how business rules are interpreted and applied while giving analysts the ability to do their own ad-hoc analysis by adding their own customizations on a per-workbook basis.

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Inheritance of updates

Once a data source has been published to the data server, workbooks using the connection automatically inherit any future updates to the data source. This greatly simplifies the process of data source maintenance,  while reducing the risk of outdated business rules persisting in production when an underlying change has been made.

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Last updated: 04 August 2023
About Author
Remy Sharp

As a Senior Writer for Mindmajix, Saikumar has a great understanding of today’s data-driven environment, which includes key aspects such as Business Intelligence and data management. He manages the task of creating great content in the areas of Programming, Microsoft Power BI, Tableau, Oracle BI, Cognos, and Alteryx. Connect with him on LinkedIn and Twitter.

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