Data Quality

The challenge

• IT is struggling to satisfy the ever-increasing business demand to make data-driven decisions.
• You may hear that the reports your business relies on are not accurate. That they require costly and time-intensive manual fixes.
• When data users do not trust your reports, they may create their own data silos in the hope of managing the quality better. Data quality issues will propagate further within the organization.
• When data is not useable by or useful to the business, it will make decisions on intuition or, worse, on wrong information.
• It all starts and ends with your data quality and understanding of what the business needs. Then you can launch initiatives to improve your business intelligence, master data management, and big data exploitation.

Our advice

Insight

• A data quality initiative is comparable to a config management initiative in that good enough is the benchmark. 100% of pure data quality does not exist. Data quality is, therefore, tolerance. Define that tolerance for each business unit before you start working on costly and lengthy data repairs.
• Remediation may cost up to 10 times more than prevention. Our blueprint will teach you how to address the root cause of data quality issues. Don't apply fixes, band-aids, and manual corrections: fix it initially, at the time of ingestion, and the process level.
• Data quality initiatives without governance are like covering the symptoms but not treating the disease. Embed data quality into your company's governance framework so that everyone thinks of data as an essential asset and treats it as such.

Impact and results 

• Align your data initiatives with your organization's strategic business objectives. You should address the practices and the data quality itself.
• Think both short and long term. Prioritize your data quality initiatives and envision the long term target-state.
• Build your related offerings in business intelligence and analytics with confidence and lowered risk because you now have a better data quality level.

The roadmap

Besides the small introduction, subscribers and consulting clients within this management domain have access to:

Get started

Our concise executive brief shows you why you should increase your data quality. Your organization already relies on it, and overall data-driven decisions will increase. We'll show you our methodology and the ways we can help you in handling this.

• Restore Trust in Your Data Using a Business-Aligned Data Quality Management Approach – Executive Brief (ppt)
• Restore Trust in Your Data Using a Business-Aligned Data Quality Management Approach – Phases 1-4 (ppt)

Define your company's data quality practices

Learn what causes data quality problems. Learn how to measure data quality health and what makes good data quality practice. Create a plan to improve where needed.

• Restore Trust in Your Data Using a Business-Aligned Data Quality Management Approach – Phase 1: Define Your Organization's Data Quality Practice (ppt)
• Data Quality Health Check Tool (xls)
• Data Quality Practice Assessment and Project Planning Tool (xls)

Define your data quality fix priorities

That is from a business perspective!

• Restore Trust in Your Data Using a Business-Aligned Data Quality Management Approach – Phase 2: Analyze Your Priorities for Data Quality Fixes (ppt)

Fix any data quality issues you have

Determine the root causes of your data quality issues and fix them there. Prioritize by most crucial business unit. Determine your strategy to resolve data quality issues. 

• Restore Trust in Your Data Using a Business-Aligned Data Quality Management Approach – Phase 3: Fix Your Data Quality Issues (ppt)
• Data Lineage Diagram Template (ppt)
• Data Quality Checklist (doc)
• Data Quality Improvement Plan Template (doc)

Embed your data quality practices

Define your continuous improvement strategy for data quality in your organizations. 

• Restore Trust in Your Data Using a Business-Aligned Data Quality Management Approach – Phase 4: Sustain Your Data Quality Practices (ppt)