META DATA MANAGEMENT

DESCRIBE YOUR DATA AND INCREASE MEANING

Meta Data Management is about getting a common understanding of the meaning of your data for both business and IT organization. Unambiguously describe business terms, policies, IT-systems, models and rules to get trust and improve usage.

With the growing volumes and usage of data in your organization it becomes important to als have a common and unambiguous understanding of your data. That starts with understanding your Metadata. Why that is important? Because it gives the people in your organization trust in the data and improves the usability.

METADATA

Your Metadata is all about defining the characteristics of your data both from a business and IT perspective:

  • What is the meaning of data?

  • Who creates, uses and owns data?

  • Where does data come from, is it used and stored?

  • Why is data used, saved and  removed?

  • When was data created, updated and will it be deleted?

The business perspective is all about how data is used on a day to day basis. It is describing business terms and the rules about how data is used. The IT perpective is about how data is structured technically, data sources, data models and so on.  Together they are indepth insight in shared corporate data assets.

A business perspective, an IT perspective or have a joined understanding?

METADATA MANAGEMENT

Well organised metadata management supports your meta data governance. It helps you to have a clear definition of all shared data assets accross your organization. In Systemation we focus on two areas of Metadata Management that support you governance.

Publishing Metadata.

Publishing the information about your Metadata to your organization. This can be done through either a Business Glossary, a Data Dictionary or a Data Catalog.

Tracking Metadata.

tracking how data flows through your organization with Data Lineage. Where does data come from, where does it go, who touches it and how does it transform along the way.

BENEFITS OF META DATA MANAGEMENT

  • Increase trust in data, stimulating usage.

  • Increase use of data, driving value.

  • Improve governance, boosting collaboration.

  • Improving regulatory compliance, reducing risk.