What are non-additive measures?

Non-additive measures are measures that cannot be aggregated across any of the dimensions. These measures cannot be logically aggregated between records or fact rows. Non-additive measures are usually the result of ratios or other mathematical calculations.

What is additive semi-additive and non-additive measures?

Types of Facts Semi-Additive: Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not the others. Non-Additive: Non-additive facts are facts that cannot be summed up for any of the dimensions present in the fact table.

What is semi-additive measures?

A semi-additive measure is one that is to be summed for some dimensions, but should not be summed across some other dimensions. For the dimensions over which the measure is not additive, a different aggregation rule must be specified.

What is the best example of an additive measure?

An additive measure uses SUM to aggregate over any attribute. The sales amount is a perfect example of an additive measure. Indeed, the sales amount for all customers is the sum of the individual sales for each customer; at the same time, the amount over a year is the sum of the amounts for each month.

How do you handle non-additive measures?

A good approach for non-additive facts is, where possible, to store the fully additive components of the non-additive measure and sum these components into the final answer set before calculating the final non-additive fact. This final calculation is often done in the BI layer or OLAP cube.

What are non-additive facts example?

Some examples of non-additive facts are average, discount, ratios etc. Consider three instances of 5, with the sum being 15 and average being 5. Now consider two numbers i.e. 5 and 10, the sum being 15, but the average being 7.5.

What is additive and non-additive facts?

Additive facts are those facts which give the correct result by an addition operation. Examples of such facts could be number of items sold, sales amount etc. Non-additive facts can also be added, but the addition gives incorrect results. Some examples of non-additive facts are average, discount, ratios etc.

What is non-additive fact in data warehouse?

Non-additive Facts are Facts that cannot be summed up for any of the dimensions present in the Fact table. Eg: Facts which have percentages, Ratios calculated. Semi-Additive: Semi-additive Facts are Facts that can be summed up for some of the dimensions in the Fact table, but not the others.

Which of the following is an example of non-additive facts?

Profit margins are non-additive. If a department has two employees, and one employee has sold an item with a 55% profit margin and the other has sold an item with a 45% profit margin, the profit margin for the department is not 100%.

What is non-additive fact with example?

Non-additive facts can also be added, but the addition gives incorrect results. Some examples of non-additive facts are average, discount, ratios etc. Consider three instances of 5, with the sum being 15 and average being 5. Now consider two numbers i.e. 5 and 10, the sum being 15, but the average being 7.5.

What are non-additive aggregates?

Non-additive aggregates are aggregate functions that produce results that cannot be aggregated along a dimension. Instead, the values have to be calculated individually. All Number functions, except for MAX and MIN, are non-additive aggregates.

How do you handle non-additive facts?

What is fully additive measure?

The most flexible and useful facts are fully additive; additive measures can be summed across any of the dimensions associated with the fact table. An example of a fully additive measure is sales (purchases from a store). You can add hourly sales to get the sales for a day, week, month, quarter, or year.

What are additive and non-additive fact?

What is the best definition of a non-additive fact?