In a scenario where Tableau Server’s dashboards are frequently updated with real-time data, what caching strategy should be employed to optimize…

For dashboards connected to real-time data, there is a fundamental trade-off between data freshness and query performance. The optimal strategy is to balance these two needs. By adjusting the cache to refresh more frequently (i.e., setting a shorter cache duration), the system ensures that users view data that is acceptably current for a "real-time" context. This approach still provides significant performance benefits by serving identical, recent queries from the cache, thereby reducing the load on the underlying live database. Tableau Server's "Refresh More Often" data connection caching setting is the direct implementation of this balanced strategy, ensuring data is re-queried from the source more frequently than the default setting.

A. A very long cache duration is unsuitable for real-time data as it would consistently serve stale information, defeating the purpose of the dashboard.

B. Off-peak refresh is a strategy for scheduled data extracts, not for live connections where data changes continuously throughout the day.

D. Tableau Server uses a hybrid of in-memory and disk-based caching for optimal performance; relying exclusively on slower disk-based caching is not a configurable or recommended strategy.

1. Tableau Server Documentation

"Configure Data Connection Caching": "For connections to data that is live and changes frequently

you may want to set the cache to refresh more often. You can do this on a per-connection basis... The available settings are low or refresh-less-often

"" (the default value

which indicates a balanced setting)

and high or refresh-more-often." This directly supports the concept of balancing and adjusting refresh frequency.

Source: Tableau Help

tsm data-access caching set command reference.

2. Tableau Whitepaper

"Designing Efficient Workbooks" (v10.0): "When connecting live

Tableau stores a cache of data for each query. This cache can be shared across different workbooks... You can configure how often Tableau Server’s cache is used by selecting a data freshness option... For data that is changing quickly

you may want to select ‘Refresh more often’."

Source: Page 18

Section: "Live connections vs. extracts".

3. Stolte

C.

Tang

D.

& Hanrahan

P. (2002). Polaris: A system for query

analysis

and visualization of multidimensional databases. IEEE Transactions on Visualization and Computer Graphics

8(1)

52-65. This foundational paper for Tableau technology discusses the importance of a responsive user interface for data analysis. It notes the performance challenges and implies the need for optimizations like caching to achieve interactivity

which must be balanced with data accuracy.

Source: Section 4.2

"Generating the visualization". DOI: https://doi.org/10.1109/2945.981851.