![]() However, because an extract is a snapshot of the data, the extract will need to be refreshed to receive updates from the original data source, whether it is a local file or an on-premise database. Instead, Tableau’s in-memory data engine queries the extract directly. As a result, Tableau doesn’t need the database to build the visualization. csv or an Excel workbook) or an on-premise database, you’re speeding up the workbook through optimization. When you create an extract from a local file (such as a. Extracts tend to be much faster than live connections, especially in more complex visualizations with large data sets, filters, calculations, etc.įor a deep dive into how Tableau extracts are created, check out Gordon Rose’s fantastic blog post on the subject. Tableau Data Extracts are snapshots of data optimized for aggregation and loaded into system memory to be quickly recalled for visualization. Extracts are one of the most powerful but overlooked tools in Tableau’s arsenal. “Extract” is a word you’re going to hear a lot in Tableau.
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