Data Governance

Good data governance obviously requires a data improvement phase. Carried out in part during the data integration phase, this often requires human interaction where automatic correction algorithms reveal their limits. 

In order to manage the accuracy, completeness, consistency and deduplication of data, Contraste assists you in putting in place a strategy and carrying out various controls. 

Contraste then supports you in developing architecture to correct data, but also to measure their quality on a regular basis. 

If your company is large, you need a system that defines several key areas of each data item: data process and sources, responsibility chain, type of information, related constraints, confidentiality levels, etc. 
We assist you in implementing this approach, including a referencing policy for these metadata. We draw up a business glossary with you to document business concepts and terminologies. The metadata will form the basis for data quality management and data governance. 

Data catalog tools also update you automatically on the various elements to be taken into account (databases, ETL jobs, modelling tools, etc.) and assemble this information in a system intend for the CDO. 

Some types of data, such as country codes and languages, are common to a company’s various applications. To put in place a real data governance system, benefit from business intelligence and the integration of applications, you need to gather the reference data in a single data source. This will enable you to manage the codification differences between applications.

Clients and product data are information that is spread across a large number of applications and databases within your company. Contraste assists you in establishing a centralised warehouse, called Master Data Management. 

The development of an MDM system establishes the processes with a view to establishing a single data source. We therefore create a reliable source which centralises a data version of the highest possible quality.