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Can any one explain me the difference between Subset ratio and information density with example.
Information density is the % of non-null values in the table
Subset ratio applies to key fields (those that exist in more than one table) and is the % of the distinct values of the field in the table of the total distinct values of the field in all tables that contain that field.
Information density:
Percentage of non-null rows in a field.
suppose field country has total 10 Records but 2 records are null then
theiw are 8 non-null values
so information density = 80 %.
Subset Ratio:
It is the ratio of distinct non-null values in a field to the total distinct non- null values in that field in entire data model
suppose table A has field country and 10 records are their
in table B country has 20 records but all records are distinct to the country field in table A
Now Subset ratio of Country in table A =distinct non - null values in country in table A / [distinct non - null values in country in table A + distinct non - null values in country in table B]
= 10/ [10+20]
=10/30
=33.33%
Hi Rohini,
you can also view the below link.
information density and subset ratio? What is the use of this?
• Information density : OF the field, which indicates the percentage of rows that contain a non-null value.
• Subset ratio: which shows the percentage of all distinct values for a field in the table compared to all the distinct values for that field in the entire data model. It is only relevant for key fields since they are present in multiple tables and do not all share the same value. Subset ratios can be used to easily spot problems in key field associations. For example, when the combined total of subset ratios for multiple tables is 100 percent, this may indicate that there are no matching keys between these tables.