Studies show that when dashboards take longer than seven seconds to respond to queries, users grow frustrated. While there are many items to try, see 33 Point Tableau Dashboard Performance Checklist, for more complex BI projects, much of the attention needs to be with how Tableau is interacting with curated data sets. Is data organized in a way that is optimized for visualization?
Creating a full 3-tier data warehouse or data mart may not always be necessary. But creating an analytics layer or third tier is the piece often ignored. Many organizations build a database that integrates various data sources, but then neglect this final layer which is a set of tables and views created and populated inside the business’ database.
The analytics layer aggregates and prepares data for consumption by a visualization tool such as Tableau. The tables and views implement structural best practices for feeding data to the visualization tool in a performant manner. This third layer could be a combination of views, tables, and possibly stored procedures built in Microsoft SQL Server. They break the “monolithic” data source into “subject matter” tables and views. These will then be combined inside Tableau or Power BI into data sources.
The end result is a Tableau data source that reads from the analytics layer and populates the data into the existing dashboards. If the Tableau data sources are properly designed and executed there should be minimal impact to dashboard designers but significant impact in both performance and insight.
Although dashboard Performance is paramount, optimization of dashboard Insight and Aesthetics are equally important LEARN MORE
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