All tagged Tableau Data Extracts
Are your Tableau extracts taking too long to generate? Are you getting asked interview questions about the process behind creating, publishing and updating an empty extract in Tableau? We've got you covered!
Check out this video to learn about an old-school method for quickly creating an extract on your desktop, publishing that extract to Tableau Cloud/Server and then updating the data once it is online.
If you want to create the best user experience in Tableau, odds are you want to convert your data connections into extracts. Tableau Data Extracts (.hyper) provide the most efficient way to query data in Tableau. Extracts are local snapshots of your data which have been optimized for usage in Tableau.
Extracts can be customized to filter data, aggregate data, and even hide unused fields. Server and cloud-based data sources can support automated extract refreshes on Tableau Server and Tableau Cloud.
I’ve been working on a project with a client for several months where we are reporting against a sizable data source. Initially that data source took about 1-3 hours to extract locally which was okay. The faster the better, but I could live with it.
It is well documented that using a Tableau Data Extractsin lieu of a live connection to a data source usually provides a faster querying experience for end users. What is not well documented are some of the errors that can pop up when working with extracts.
