If we have 2 files that we want to bring into tableau and use both files our analysis, there are different ways to do this depending on what you want to look at.
Firstly, you have to make sure the granularity of both data sets are the same otherwise it will cause tableau to give you an incorrect analysis or end up breaking.
What is granularity?
Granularity in simple terms is how detailed the data is.
- The more detailed, the higher the granularity. (Hence the more rows of data you will have)
- The less detailed, the lower the granularity. (Vice versa, the less number of rows of data you will have)
If you want to know 'How granular is your data?' as yourself, what does one row of data represent.
Why is Granularity important?
As stated earlier, if the granularity for both datasets are not the same when linking the two, you will run into a lot of errors and/or incorrect analysis.
Now lets look at an example:
I want to compare between the sales and target data for each company over month/year.
Looking at these dataset, what issues do we have? If we want to be able to compare/use both these datasets in our analysis, the major issue we have is the different data levels/granularity.
- Sales data is at a DAY level
- Target data is at the MONTH level
- Target data is missing 2013 values
- Target data has values that maybe looks into the future?
So how do we fix this?
There are 3 ways to fix this issue.
- Using Relationships
- Using a Join and then LODs
- Blending the 2 data sources together
