Dealing With Data Quality Problems In Tableau
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In this Tableau article, we are going to learn to solve data Quality problems which we usually face during the use of Tableau. In this article, we will learn the basic Solutions to solve the data quality problems.
2. How to Deal/Solve Data Quality Problems in Tableau
Incorrect information can prompt terrible choices. A scene is great at imagining information and making it reasonable. In the event that your information isn’t perfect—when you associate Tableau to it, you will see the issue unmistakably. Luckily, Tableau gives devices to enable you to bargain with issues that don’t require intercession at the database-level to determine (at minimum incidentally) unclean information issues. In any case, the best game-plan when you discover mistakes is to report them to the IT individual in charge of information quality inside the database you are utilizing.
REad more about Tableau Design Flow & Navigation
3. Basic Quick Solution for Data Quality Problems
There are several different ways to correct data Quality problems within Tableau that don’t involve changing the source data.
Renaming fields in Tableau are finished by right-tapping on the field and renaming it. Field part names can be associated. These progressions don’t change the source database. Scene “recalls” what you renamed without modifying the source information.
For more detail check the previous article Renaming Worksheet in Tableau
How about we expect that an organization name has been entered as these: A&M, An and M, An and M, A+M. With Tableau, you can Ctrl-Select every one of these names and aggregate them—and afterward make a name assumed name for the specially appointed gathering. Along these lines, all the renditions of the name show up as one record in Tableau—A&M. This gathering what’s more, name false name will be spared as a major aspect of Tableau’s metadata.
At times the name of something in the database isn’t a helpful term for detailing purposes. For instance, everyone on the group enters the client type as P1, P2, G1, G2 where P2 indicates the extent of the client in yearly income. For instance, “Platinum level 2” could imply that the client has a yearly income of $1m to $5m. In Tableau, you can right-tap on P2 and nom de plume it with a more significant depiction.
d. Geographic Errors
Despite the fact that Tableau has worked in mapping that works extremely well, there will be events when geographic areas are not perceived. A scene will caution you by putting a little dark pill in the lower right region of your guide. Clicking on that pill gives the capacity to alter the culpable areas or channel them out of view. This is likewise available from Tableau’s guide menu.
e. Null Values
When you see the word invalid show up in a view that implies Tableau can’t coordinate the record. You can sift through nulls, bunch them with non-invalid individuals from the set, or right the join that is causing the invalid. There are numerous reasons why an invalid esteem could come about. In the event that you aren’t sure how to amend the invalid, look for help from a qualified specialized asset.
f. Correcting Your Data Source
In spite of the fact that it’s fast and simple to address information quality issues specifically in Tableau, it’s critical to hold up under as a top priority that the progressions you have made in Tableau will just advantage those utilizing a similar Tableau document. There is not a viable replacement for remedying the basic information in the data source. Report blunders to the dependable staff rapidly and give them your Tableau report. Uncover the points of interest to rectify the database.
Read more about Tableau data source
In this tutorial to deal with problems that we deal with Data Quality Problems in Tableau, we learned about the quick solutions that are offered by Tableau to solve these Data Quality problems. This tutorial marks the completion of yet another milestone in our journey. Furthermore, if you have any query, feel free to ask in a comment section.
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