A metadata management system is the heart of data governance. But it’s not enough.

Data Management and Data Governance Data Management and Data Governance

What are the IT functional components for data governance?

Governing a company’s data means executing a series of specific processes, which consume and produce information (in this case metadata) and are often supported by indicators. At the center of it all is a metadata management system. It contains all company data in the form of entities, their attributes and mutual relations.

According to classical taxonomy we can classify this metadata into three different but interconnected types:

  • business metadata (collected in a business glossary – For example: business terms, semantic ownership, connected processes and rules),
  • technical metadata (metadata dictionary – For example: physical fields, lengths and formats, computer applications and automatic controls),
  • operational metadata (For example: arrival of flows, completion of transformation processes, results of controls in a given period). The interconnection between these three areas of government is an essential point.

All the information for the execution of data governance processes, and more generally data management, are recorded in this functional component.

What features must a metadata management system have?

One important requirement is to be open to connection along two dimensions and in two directions. The first dimension is “horizontal” with other repositories that record information relating to entities that have relations with data (such as processes, applications, organization charts) often managed in dedicated applications. The second is “vertical” with the physical world or, more precisely, with operational,data management tools: data integration, data quality, data profiling, data discovery and data masking.

With both types of instruments, metadata management system must have a two-way dialogue:

  • gathering, for example the metadata related to a process (name, description, owner, …), so that it can be integrated with information related to input, output or internal data of the process,
  • providing data discovery engine with search rules for a business term, if the discovery is successful, the name of the physical fields that represent that business term in IT systems will return. And so on.

A look into the future…

Another increasingly important feature of this component is the ability to adapt to the evolutions of the data governance model. Frequent revisions of company processes, the introduction of new regulatory requirements (increasingly data intensive) the need to support internal initiatives such as: those aimed at digital transformation of the company, require not only content change , but also the structure of metadata management system: adding new entities, attributes and relationships to the metamodel.

What are the useful elements to offer valuable business services?

As mentioned above, the medadata management system is only one component of an instrumental data governance architecture. Other functional modules are very useful, and in some cases necessary: ​​a calculating system, representing, distributing performance indicators (KPI) of governance (coverage, maturity, program management) and perspective (quality, but not only ); a workflow management system capable of orchestrating automatic activities and human tasks in the data governance processes execution.

But it is the fluid interaction between these modules makes the real difference; the possibility of building functional blocks by combining metadata management primitives, process orchestration, performance analysis allows to automate and support “service oriented” data governance processes based on the “declarative” paradigm, which expose specialized services able to transparently manage articulated and complex operations.