Ten Steps to Quality DataAri Hovi Oy
Ten Steps to Quality Data
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Ten Steps to Quality Data
We live in a data‐dependent world. We MUST have data and information to survive. And the better the quality of the data, the better we can make decisions and take effective actions for the sake of our societies, families, ourselves as individuals, and our organizations. The need for high‐quality, trustworthy data in our data‐dependent world will not go away. This course provides not justwhatshould be done, buthowto address the problems of poor‐quality data.
Simply put, information quality is providing the correct set of accurate information, at the correct time and place, to the correct people. However, ensuring quality information is far from simple. Whether you are just starting a project or are already in production, it is not unusual to find that data quality issues prevent organizations from realizing the full benefit of their investments in business processes and systems.
Join us to learn the Ten Steps to Quality Data and Trusted Information™ – a practical approach to creating, improving, and managing the quality of information critical to running your business, satisfying customers, and achieving company goals. If you are working on real data quality‐related issues that need real results, this is the course for you. What you learn here applies to all kinds of data and every type of organization – for‐profit businesses of all sizes, education, government, healthcare, and nonprofit – because all depend on trusted information to succeed.
Both foundational data quality concepts and practical instruction are included. Be prepared to participate as this is a highly interactive course. Class discussion and exercises (both individual and with teams) are an integral part of the seminar. In addition, attendees have the opportunity to apply what is learned to a course project, chosen from their real data quality situations and concerns. Come with your particular needs in mind, learn how these topics apply to your situation and leave with realistic methods for improving information quality.
What You Will Learn
After attending the Ten Steps to Data Quality course, attendees will: Have the background needed to conduct their own data quality project using the Ten Steps methodology ‐ a proven approach for creating, improving, sustaining, and managing data and information quality within any organization
Through presentation, group and individual exercises, and a course project, attendees will learn how to:
- Turn data quality challenges into actionable projects that will address critical business needs
- Use business impact techniques to show the value and impact of data quality
- Use data quality dimensions to assess the data that supports business needs and project objectives
- Use root cause analysis techniques to address the true causes of data quality issues
- Use the Ten Steps methodology to create solutions for a variety of issues and concerns (large and small)
- Fit data management topics such as data governance, data modeling, metadata, business rules, master data, reference data, and data standards into the process for ensuring high quality data
- Apply concepts such as the Framework for Information Quality and the information life cycle to data quality management
- Apply templates and examples to address their own data quality concerns
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Danette McGilvray is president and principal of Granite Falls Consulting, Inc., a firm that helps organizations increase their success and enhance the value of their information assets by addressing the information quality and data governance aspects of their business efforts.
Danette is the author ofExecuting Data Quality Projects: Ten Steps to Quality Data and Trusted Information™, (Morgan Kaufmann Publishers, 2008 and 2021). She has trained Fortune 500 clients and workshop attendees around the world, her book is used as a textbook in university graduate programs.
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