Not having a business-aligned data quality management approach results in:
- Unclear definitions of what tolerance for data quality is and how it differs across business units according to their needs.
- Difficulties getting past a “band-aid” level of data quality solutions, as the issues continue to crop up even after an attempt has been made to repair data quality.
- Difficulty understanding the root causes of these issues.
Having a business-aligned data quality management approach results in:
- Good data quality, allowing you to generate insights into customer intimacy, operational excellence, and innovation leadership.
- Effective data quality improvement projects driven by business need for data.
- A corporate culture that holds data quality as a priority and data as a key asset.
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Book NowModule 1: Define Your Organization’s Data Environment and Business Landscape
The Purpose
- Evaluate the maturity of the existing data quality practice and activities.
- Assess how data quality is embedded into related data management practices.
- Envision a target state for the data quality practice.
Key Benefits Achieved
- Understanding of the current data quality landscape
- Gaps, inefficiencies, and opportunities in the data quality practice are identified
- Target state for the data quality practice is defined
| Activities: | Outputs: | |
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| 1.1 | Explain approach and value proposition |
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| 1.2 | Detail business vision, objectives, and drivers |
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| 1.3 | Discuss data quality barriers, needs, and principles |
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| 1.4 | Assess current enterprise-wide data quality capabilities |
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| 1.5 | Identify data quality practice future state |
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| 1.6 | Analyze gaps in data quality practice |
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Module 2: Create a Strategy for Data Quality Project 1
The Purpose
- Define improvement initiatives
- Define a data quality improvement strategy and roadmap
Key Benefits Achieved
- Improvement initiatives are defined
- Improvement initiatives are evaluated and prioritized to develop an improvement strategy
- A roadmap is defined to depict when and how to tackle the improvement initiatives
| Activities: | Outputs: | |
|---|---|---|
| 2.1 | Create business unit prioritization roadmap |
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| 2.2 | Develop subject areas project scope |
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| 2.3 | By subject area 1 data lineage analysis, root cause analysis, impact assessment, and business analysis |
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Module 3: Create a Strategy for Data Quality Project 2
The Purpose
- Define improvement initiatives
- Define a data quality improvement strategy and roadmap
Key Benefits Achieved
- Improvement initiatives are defined
- Improvement initiatives are evaluated and prioritized to develop an improvement strategy
- A roadmap is defined to depict when and how to tackle the improvement initiatives
| Activities: | Outputs: | |
|---|---|---|
| 3.1 | Understand how data quality management fits in with the organization’s data governance and data management programs |
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| 3.2 | By subject area 2 data lineage analysis, root cause analysis, impact assessment, and business analysis |
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Module 4: Create a Strategy for Data Quality Project 3
The Purpose
Determine a strategy for fixing data quality issues for the highest priority business unit
Key Benefits Achieved
Strategy defined for fixing data quality issues for highest priority business unit
| Activities: | Outputs: | |
|---|---|---|
| 4.1 | Formulate strategies and actions to achieve data quality practice future state |
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| 4.2 | Formulate a data quality resolution plan for the defined subject area |
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| 4.3 | By subject area 3 data lineage analysis, root cause analysis, impact assessment, and business analysis |
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Module 5: Create a Plan for Sustaining Data Quality
The Purpose
- Plan for continuous improvement in data quality
- Incorporate data quality management into the organization’s existing data management and governance programs
Key Benefits Achieved
- Sustained and communicated data quality program
| Activities: | Outputs: | |
|---|---|---|
| 5.1 | Formulate metrics for continuous tracking of data quality and monitoring the success of the data quality improvement initiative |
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| 5.2 | Workshop Debrief with Project Sponsor |
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| 5.3 | Meet with project sponsor/manager to discuss results and action items |
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| 5.4 | Wrap up outstanding items from the workshop, deliverables expectations, GIs |
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