Business data governance is a very important subject that is often neglected, even though it is paramount for efficient data integration. Taking care of data governance means carefully defining data usage and management, agreeing to processes for handling data issues and boosting the quality of your data so your business decisions are based on real, correct and up-to-date assets. Having the right technologies, smart tools and the right people with you during this data governance process is the key to success.
We start with a stock taking survey, checking your data quality, your data life cycle and business processes and your technical and organisational capabilities. With this clear picture, we gain insights and derive a smart data governance strategy including policies, data architecture, priorities, business cases, data standards and your desired data status. At the same time, we start with the Define process as the outcomes of both processes influence each other.
This phase focuses on understanding your business context. We dive into your data definitions and business terminology, gather insight in how you use taxonomies, which relationships occur, and how policies, standards, rules and processes work together. A clear measurement strategy defines the data governance efforts. The Discover process is running at the same time, influencing the results of the Define phase.
As a third step, we make sure that all data governance policies, processes, business rules, cross-functional roles and responsibilities as well as workflows are included in the Define and Discover phases.
Once the data governance strategy is implemented, we make sure that it is effective and the stewardship efforts generate value. By continuously monitoring data governance compliance and exceptions from the rules, we keep the strategy, your data life cycle and your data assets up to date, audtiable and transparent.
Master data governance is a discipline that is implemented across organisations via an ongoing and evolving program made up of technologies (software solutions such as SAP’s MDG), subject matter experts and a focused project to enforce MDG. An MDG program is more than just the implementation of the technology. The greatest challenges will not be technical, but data governance-related. The creation of an appropriate, well-functioning data governance mechanism is essential for the success of an MDG program. It needs to ensure strong alignment with the organisation’s business vision and demonstrate on-going value through a set of metrics.
1: MDM vision
2: MDM strategy
3: MDM governance
4: MDM organisation
5: MDM processes
6: MDM technology infrastructure
7: MDM metrics