Depending on the logical data, the structure of a database for a management element supported by performance indicators can be used. The newly acquired data architecture makes it ­possible to obtain measurable cost savings and cost reductions. The business risk is lessened because the business processes between business and IT have been optimized. New guidelines can be applied in the area of process, data, and application ­integration on the basis of the EA approach, creating new structures which improve and increase data quality. Interface issues and access rights can also be improved across all of the organizational boundaries. 

Especially midsize and large companies can make use of a ­compliance and governance strategy to regulate the processes, roles, and responsibilities. The transparency created with respect to everyone involved makes the processes more secure for the future and permits a modification of the data landscape only by following the defined procedures. Obtaining – and securing – an overview of the data landscape is possible only by means of a structured procedure.  

Data governance minimizes business risk 

A comparison of a one-time snapshot with a “data map” shows that the data map also picks up on changes in business processes. Despite the integrated systems at the process level, these data are distributed over various data landscapes with independent source systems. Data quality is often inconsistent and poor, including redundant or contradictory information. In large companies with multiple layers of product and organizational structures, data are frequently highly heterogeneous.  

Every attempt to establish a structure, order, and an overview has often failed because of the obsolete data. A data landscape commonly lags behind the “dynamics of the business processes” and is not as up to date as it actually should be. This circumstance of “up-to-date data” is a business risk which companies must keep as small as possible.  

Data governance provides the implementation of the data ­models and structures. It gives transparency to a company’s data flow, and the breakdown of data into areas with primary and secondary data can be carried out. The question of the owner of the data is clarified generally with respect to the data, data and activities can be attributed. Furthermore, it is possible to model a relationship between business processes and the functions to be realized with the data required for this purpose.