For these analytics, using an extract of the data source helps build a faster workbook. But in the same hospital, there may also be visualizations that monitor daily or weekly trends. These situations necessitate a live database connection. Hospitals that monitor incoming patient data need to make real-time decisions. Workbook speeds are affected by a variety of factors, including your network speed, traffic on that network, and any custom SQL.īoth types of connections have their place.
There are also more variables at play when using a live connection. With live connections, your data queries are only as fast as the database itself. And unlike extracts, databases are not always optimized for fast performance. But live connections also rely on the database for all queries. Live connections offer the convenience of real-time updates, with any changes in the data source reflected in Tableau. 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. For a deep dive into how Tableau extracts are created, check out Gordon Rose’s fantastic blog post on the subject. Extracts tend to be much faster than live connections, especially in more complex visualizations with large data sets, filters, calculations, etc.
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. Reference Materials Toggle sub-navigation.Teams and Organizations Toggle sub-navigation.
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