Fix It Yourself: Improving and Monitoring the Quality of Your Data
Overruns, account errors, audits, theft, missing inventory, overtime pay, employment discrimination, government regulations, and compliance rules. Any and all of these explain why data quality is critical to a business. More expansive reporting requirements and data privacy restrictions require more thorough and accurate data management. Corporate fraud and mismanagement, either hidden by lax data control policies or caused by reliance on inaccurate data, wreak havoc in the marketplace. Everyday profitability and competitive advantage are challenged by inaccurate, untimely and unavailable data. What can you do? What should you do?
Claudia Imhoff will discuss the risks and consequences of relying on poor-quality data. Learn ways to measure and monitor your data quality to determine if you're satisfying your data quality requirements. These include data lineage, impact analysis and data profiling. Find out how you can identify and encourage data accountability company-wide.
High-quality data is no guarantee that you'll be safe from all the dangers of fraud and mismanagement, but an effective data management policy that supports a data stewardship strategy can minimize the chances of finding your business on the wrong side of the road.
You Will Learn:
- Financial, operational and legal risks of relying on poor-quality data
- How to measure the impact of "non-quality"
- How to bridge the gap between business and IT with collaborative solutions for driving information management initiatives
- Best practices for governing enterprise information and improving information transparencyli>
Claudia Imhoff, Ph.D.