Data Ed Online: Engineering Data Quality A Framework for Effective Data Management

High-quality data is essential for effective data management strategies, which can lead to significant procedural improvements and increased profit margins. Engineering data quality provides a framework for utilizing data quality management effectively in support of business strategy. This approach allows for the quick identification of business problems, differentiation between structural and practice-oriented defects in data management, and proactive prevention of future issues. Organizations must understand the importance of utilizing data quality engineering to support their business strategy.

This webinar will demonstrate how chronic business challenges often stem from poor data quality and will illustrate how engineering data quality provides a useful framework for developing an effective approach. This, in turn, enables organizations to quickly identify business problems and data issues caused by structural or practice-oriented defects, preventing their recurrence.

Learning objectives:

• Help you understand foundational data quality concepts for improving data quality at your organization
• Demonstrate how chronic business challenges for organizations are often rooted in poor data quality
• Share case studies illustrating the hallmarks and benefits of data quality success

Download the slides here: https://www.dataversity.net/sep-9-dat...

The Developing a Data Quality Learning Plan, led by instructor Mark Horseman, equips participants to design and launch data quality programs with precision, blending governance principles, ownership models, and actionable frameworks. Sign up today: https://training.dataversity.net/lear...