Data Governance Jump Start
Master data management is receiving increasing attention from both business and IT executives. Companies have become more attuned to the importance of reliable data within enterprise systems. The detrimental impact of poor quality data on critical business processes and more stringent regulatory reporting standards have combined to encourage companies to consider implementing a master data governance program – many for the first time.
But some very important questions need to be answered before getting started:
Data governance is not something that can be driven by technology. Indeed, it is impossible to even define the need for technology until some fundamental questions about data governance have been answered.
Data Governance Jump Start is a unique program that will define the need and scope of data governance from a business perspective. Jump Start enables an organization to:
- Define its requirements within the context of business processes.
- Identify actual issues within the current business data.
- Create a data governance roadmap with realistic goals and timelines.
- Build a business case for a data governance program.
Data Governance Jump Start is an efficient process for an organization to define its requirements for data quality. The Jump Start analysis also creates a framework for measuring ROI for the resulting implementation plan.
The MDX-based Jump Start process minimizes the impact on business users and ensures that the data governance requirements are practical and based on real data issues.
Data Governance Jump Start Process
Define
The business defines its requirements for data quality and availability within a business process context. At the same time, information relating to the direct and indirect cost of data quality deficiencies is gathered.
Capture
The business requirements for data quality are stored in the MDX repository. The repository maps the relationship between a data element, business process and business owner.
Apply
The current business data is profiled against the requirements. This data profiling goes far beyond the typical checks for population and domain values; Jump Start profiling also identifies specific use-cases that relate to data quality issues.
Review
Business owners will review the use-case data to validate or refine their requirements. Additional issues that were not initially visible to the business will be highlighted and the data or process owners will be asked to provide additional guidance on how these issues should be handled.
Plan
A plan for ongoing data governance is the final deliverable of Jump Start. The plan will consider the gap between current data quality and data quality requirements along with the costs and opportunities associated with closing these gaps.
All organizations manage data quality to some degree – existing systems and processes will have evolved some capacity to identify and fix data quality. We also know that all of an organization’s data does not need to be completely correct, all of the time. Indeed, perfect data is impossible (certainly impractical) to achieve over a sustained period of time.
The goal of a successful data governance program is to:
- Find the optimal balance between the benefits of improved data quality and the cost of
maintaining this level of quality.
- Implement systems to achieve this level of data quality.
- Implement a data governance program that maintains data quality and reduces costs
over time.
Data Governance Jump Start provides the ideal starting point for this roadmap.
Data Governance Roadmap
