Like other analysis types covered in the chapter, Filtration analysis allows you to place filters for your queries. Applying filter can be seen both for 'exclusion' OR 'selecting specific values for inclusion'. In simplistic way, filtering can be equivalent to 'where' clause of an SQL query.
Here are different ways you can Data Filtration analysis:
Data Filter on specific values of a dimension by direct specifications:
Calculating sales for select set of offices in a city OR calculating the operating expense across a given set of expense lines. The filtration can be on combination of dimensions- For example- select set of office locations, which are selling a given line of products.
Data Filter on specific value of a dimension given a certain conditions, related to a dimension:
Calculating average sales revenue for only those office locations, which have been operating for less than 6 months of time. There can be more complex conditions.
Filter on specific values of a dimension linked to measure values:
Calculating average sales value productivity for only those offices, where the sale is less than the average sales per office across all the offices.
Filteration analysis on tolerances and outliers:
When you are calculating the averages (say), you may like to count out the values, which are below certain tolerances (outliers). For examples, calculation of average write-off values from cancelled credit cards, where the write-off is more than USD 10 dollar and less than USD 20000. Top and bottom filters:
Example-Filtering out the 'top 10', 'bottom 10', 'top 10%', 'bottom 10%'. |
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