Data governance strategy
An organisation begins its data governance journey by defining the business goals it wishes to achieve by implementing data governance and how it plans to use corresponding performance metrics to track the progress and milestone achievements during its data governance journey.
Enterprise data management
This component covers all the key areas which would be essential for any typical organisational data ecosystem. For example, data architecture management, data models, data integration, metadata management, reference data management and business intelligence/analytics are part of enterprise data management.
Data lifecycle management
It is a policy-based approach to manage the flow of an information system’s data throughout its lifecycle – from creation and initial storage to the time when it becomes obsolete and is deleted. It combines data processes, business strategies and technologies so that the strategic combination of all three could have the necessary impact on the organisation. Once a sound data lifecycle management strategy is in place, an enterprise can reap significant benefits including better accountability, higher compliance, cost savings, efficient organisational governance, better data protection and greater reporting integrity.
Data stewardship and core functions
It covers core areas which should be prioritised for the successful execution of any data governance programme. Organisation should also decide on various Key performance indicators (KPIs) across productivity, brand equity and performance to measure data governance program. Governance operations cover more granular functions like business glossary set-up, metadata management, data lineage, data quality, data privacy and security and data access and control.
Data governance enablers
The components of the data governance framework explained above revolve around three key pillars of the governance – people and culture, process and operating models, and tools and technology. Before beginning with any data governance programme, organisations need to assess their current maturity and processes around how they handle their data assets, identify gaps in handling data and come up with relevant solution designs and a roadmap for governance implementation.
Apart from the above explained components, PwC’s Data Governance Framework can also help organisations with some support functions like change management, stewardship and user adoption guidelines so that organisations can adapt the framework smoothly across the enterprise, without any hurdles.
