Why are OLAP cubes used


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OLAP is the abbreviation for Online A.nalytical P.rocessing. This is understood to mean a certain type of database in which - in contrast to transaction-oriented systems (e.g. making bookings or orders) - the evaluation of existing databases is in the foreground. This technology, which was developed by Edgar F. Codd in the 1990s, is based on a special type of data storage multidimensional data modeling. This allows you to evaluate, for example, sales or contribution margin sizes with regard to several - previously self-defined - dimensions: for example per product, per customer, per region or distribution channel.

Cubes, so-called cubes, are often used for visual representation "OLAP cubes". With this “paper-based” mapping, however, one is limited to three dimensions; this does not apply to OLAP technology. Ten to fifteen dimensions in a data cube are not a problem for most of the programs available on the market. The number of possible dimensions also depends on the number of characteristics per dimension (= elements). Example: The dimension “type of number” could include plan, actual and forecast values.

OLAP systems either obtain their data directly from operational upstream systems (also ERP systems called - "E.nterprise R.esource P.lanning "). This mainly happens when only a small amount of data is to be processed. In the case of larger databases, you are happy to import from a central one Data warehouse ("Data supermarket"). The data from mostly several previous systems are periodically transferred there and kept redundant. The data warehouse is installed separately from the upstream systems on specially designed hardware (server).

OLAP tools offer a particularly great advantage when carrying out complex analyzes that cause a very high volume of data, because the access times are well below those of conventional relational databases. This is because such systems are geared towards mass data management and less towards reporting and analysis options.

OLAP systems as part of Business Intelligence (BI)

BI systems are planning, analysis and reporting tools that help controllers to organize their core tasks in these areas more effectively and efficiently. With the help of a correct use of BI systems, the following advantages can be achieved, for example:

  • Time savings with standard reporting through automated interfaces and thus reduction of the error rate of the process (fast close)
  • Better analysis options, e.g. through the use of Data mining systemswhich automatically show previously undetected, but important anomalies within a large database
  • flexible and fast ad hoc reporting
  • Improvement of the quality of the information preparation through the simple presentation of tables and graphics
  • Personalized data access via intranet or web browser
  • Shortening the planning process through simple decentralized recording (usually Excel as a front end tool) and consolidation of the planning data.

The amortization times of BI systems are often one to three years. We can therefore expect even greater use in the next few years.


Controller Handbook, 6th edition rewritten, Verlag für ControllingWissen AG, Offenburg, 2008

First-time writers

Albrecht Deyhle, Controller Academy

Gerhard Radinger, Controller Academy