Common Data Warehouse terms

A short description of the most central terms will help you to understand the elements you will across when working with data warehouses for the TARGIT Decision Suite.

Business Intelligence

Business Intelligence, basically, is a matter of providing insight into an organization’s business data in an easy to overview manner, thereby enabling you to make the right decisions and lay down the right strategies during a hectic workday.

Data Warehouse

A Business Intelligence solution is typically based upon a Data Warehouse, which is a database that collects and refines data from one or more source systems. Examples of source systems could be MS Dynamics NAV, Axapta or similar ERP systems. Often, this Data Warehouse will come in relational versions as well as a multidimensional version.


Cubes are the way to organize data in a multidimensional Data Warehouse. In addition to a well-defined data structure, the cubes also ensure that end-user requests for data is processed with optimal performance. The cubes are visible to the end-users, and each cube will typically contain data for one well-defined business area like Sales, Finance, Inventory etc.


Generally, you define a cube by defining the Measures and the Dimensions it should be built upon. The measures are the factual data upon which you want to make analyses and reports. Synonyms for Measures might be KPIs or “the interesting numbers”. E.g. in Sales cube you would see measures like Revenue, Costs, Profits, Budget etc.


You use Dimensions to categorize or to view your data from specific angles or from specific perspectives. E.g. in a Sales cube you would have dimensions like Products, Customers, Salespersons, Time etc. You also use dimensions for setting up criteria or filters on the data your examining, e.g. for seeing data of a specific Product Group or across a specific time span.

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