How and Why to Create Tableau Data Extracts (.hyper)
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- Опубліковано 8 чер 2024
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Description:
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.
If you're ready to take your Tableau development experience and end-user experience to the next level, check out this video on how to convert your data connections to Tableau Data Extracts!
Resources:
•Mariners 2023 Example Data: www.baseball-reference.com/te...
•Google Sheet IMPORT Functions: onenumber.biz/blog-1/2021/6/9...
•Tableau Prep Living Connections: onenumber.biz/blog-1/2021/5/1...
•How to Generate Tableau Extracts Faster: onenumber.biz/blog-1/2021/3/1....
Chapters:
0:00 What is a Tableau Extract?
1:18 How to Initiate an Extract
2:20 Logical vs. Physical Table
3:00 Example Data Exploration
4:38 Aggregation Option
5:13 Number of Rows
5:58 Hide all Unused Fields
7:00 Creating the Extract
7:28 Unhide Fields
8:42 Incremental Refresh
10:00 Refresh Extract in Tableau Desktop
10:35 Publish Extract
12:45 Automating Extract Refresh
14:23 Where is a local Extract saved?
15:14 Extract History
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Perfect Session. You literally answered all my questions regarding this subject as you go! Thanks alot.
Amazing, we're so glad this helped. Thank you for letting us know!
Thank you for this free video lesson.
Absolutely!
Many thanks for this comprehensive run through. How does the scheduling of refreshing extracts this way using tableau cloud differ from using Tableau Bridge. Is it to do with Online vs Server?
You are welcome! Tableau Online and Tableau Server should offer roughly the same options for scheduling extract refreshes. Ultimately, some of the fine details might be up to your Administrator however. I think if Tableau Bridge is implemented correctly, you should be able to utilize refreshes from there as displayed in this video. There are a few limitations (120 minute refreshes maximum) when it comes to Bridge that you can read up on here: help.tableau.com/current/online/en-us/to_bridge_eds_performance.htm#:~:text=To%20ensure%20that%20long%2Drunning,120%20minutes%20for%20refresh%20tasks.
I have a question about setting up scheduled refreshes. I am creating my dashboard from an XLSX file that I update by running through my python script every morning. Its not convenient I know but due to constraints in the data infrastructure at work this is what I need to do. So every morning I run the file through my script, then go to tableau and refresh my extract, then I republish. My question is that if I set up the automatic refresh, will tableau refresh the extract by looking at the file in my desktop, or will I still need to go into tableau and refresh the data manually for my published workbook to be using the most up to date data?
Unless you are publishing that Excel file to an accessible location (Directly to the Server, OneDrive, Shared Drive, into the database), Tableau Server isn't going to be able to refresh an Excel file from your local PC. However, Tableau Bridge might give you a workaround if something like that is needed: help.tableau.com/current/online/en-us/to_sync_local_data.htm
Hey! nice session, but could you help with how to use extract when you've paramters like date parameters in your workbook?
Hi! I don't see how having Date Parameters in your workbook would limit your use of an extract unless those parameters are being referenced in a Custom SQL Statement. Is that how you are using them?
Yes, I am..you got it right..
Didn't feel the need to mention that am using custom sql with parameters, since I had no idea this info will make any difference😢.
Anyways..pls pls help me in this situation..we need to have extract as the report performance is affected with live connection.
@@kanikasuneja7777 You won't be able to have dynamic parameters tied to Custom SQL and extract at the same time sadly. Maybe you can improve the data source performance by hiding unneeded column or filtering unneeded rows?
my biggest reason to use an extract is because "distinct count" is only available in extracts
Fair enough! That's a pretty significant bonus as well.