What is non-additive measure?
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 are non-additive facts in data warehouse?
Non-Additive: 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.
What is a measure in OLAP?
Most often, OLAP measure meaning is a numeric value by which the dimension is detailed or aggregated. It specifies a certain OLAP dimension and answers the “How much…?” question. For example, information about totaled bike sales is set out in one of the measures.
What is additive fact in data warehouse?
Additive: Additive facts are facts that can be summed up through all of the dimensions in the fact table. 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.
What is factless fact table with example?
A factless fact table is a fact table that does not have any measures, i.e. any numeric fields that can be aggregated. For example, if you are modelling product sales, you can have a Sales fact table that will contain the dimension keys and, for example, the “amount” value/measure, to record the amount sold.
How is database represented on OLAP?
OLAP Metadata Model. The basic data model in a relational database is a table composed of one or more columns of data. All of the data is stored in columns. In contrast, the basic data model for multidimensional analysis is a cube, which is composed of Measures, Dimensions, and Attributes.
What are the different types of facts in data warehouse?
There are three types of fact tables:
- Transaction Fact Table. The transaction fact table is a basic approach to operate the businesses.
- Snapshot Fact Table. The snapshot fact table describes the state of things at a particular time and contains many semi-additive and non-additive facts.
- Accumulated Fact Sheet.
What is OLAP operations?
OLAP stands for Online Analytical Processing Server. It is a software technology that allows users to analyze information from multiple database systems at the same time. It is based on multidimensional data model and allows the user to query on multi-dimensional data (eg. Delhi -> 2018 -> Sales data).
What is OLAP data?
OLAP databases contain two basic types of data: measures, which are numeric data, the quantities and averages that you use to make informed business decisions, and dimensions, which are the categories that you use to organize these measures.
What is a cube in OLAP?
OLAP databases are divided into one or more cubes, and each cube is organized and designed by a cube administrator to fit the way that you retrieve and analyze data so that it is easier to create and use the PivotTable reports and PivotChart reports that you need.
Which measures are completely non-additive?
Finally, some measures are completely non-additive, such as ratios. 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.
What are server actions in OLAP?
Server Actions A server action is an optional but useful feature that an OLAP cube administrator can define on a server that uses a cube member or measure as a parameter into a query to obtain details in the cube, or to start another application, such as a browser.