In today’s modern tech world, everyone expects more. Every one wants to be able to feel and touch their data. That is exactly what “Visual filtering” allows you to do.
you click on a data element and all the other reports are showing only contextual data.
Once your audience starts using visual filtering, the entire perspective on data changes.
Here’s an impact story:
One of my customers implemented a snr leadership facing dashboard and they recently conducted a meeting where not only did they use the Tableau dashboard to provide info, they decided to actively participate in some slicing and dicing of the data on the dashboard using “visual filtering”
This is the dream
One of the other execs in that meeting upon seeing the power of visual analytics
So, you got access to data, you know what you need from the data source and you are off to the races, building Tableau dashboards
EXCEPT, each one of your queries takes a long time to execute on the DB.
Here are some ideas around how to get past those issues:
If you are told that the DB is well tuned, but it is NOT giving you the performance you need, you need to take the situation in your hands, right? That’s when Tableau extracts can help you out.
If you are given a very complicated SQL that you don’t know how to reconstruct using Tableau visual joins, go ahead and plug in the SQL into the CUSTOM SQL view, and then extract the data
If you are told that the final dashboards needs to be on live data but you need to create dashboards while the DB is being tuned, extract thed ata
If you need to work offline on developing something, extract the data
As you can see there are many scenarions you need to extract the data, but for some reasons, the biggest reason that I STILL see in the field is that many databases are still not tuned for modern analytics that Tableau provides. In that case, we just need to extract the data out
Tableau extracts can make a huge different to your analytical queries as it is a columnar data store. If your data privacy and policies permit, consider using extracts instead of live database connections. Most definitely helpful during dashboard design phases even when final product needs to be based on live data
PRO TIP: Hiding unused fields from the data source can make a huge impact