Today many corporate boards and executives understand the importance of data for improved business performance. However, most of the data in enterprises is of poor quality. According to a report in Harvard Business Review, just 3% of the data in a business enterprise meets quality standards. However, there are many myths associated with realizing data quality and this is creating misconceptions on data quality. Against the backdrop, this webinar looks at three important data quality myths and their corresponding realities. It also offers prescriptive recommendations for business enterprises to improve the data quality.
• Data Quality definitions
• Key data quality dimensions
• Three Common Misconceptions About Data Quality
• Impact of Misconceptions on Business
• Best Practices to Improve Data Quality
• Case Studies and Success Stories for Data quality Improvement
Dr. Prashanth H Southekal is the Founder of DBP Institute a Data and Analytics Consulting, Research, and Education firm based in Calgary, Canada. He is a consultant. author, keynote speaker, and professor of Data and Analytics. Dr. Southekal has advised over 80 organizations including P&G, GE, Shell, and Apple. He is the author of three books — “Data for Business Performance”, “Analytics Best Practices”, and “Data Quality” and writes regularly on data, analytics, and machine learning in Forbes, SAP Insider, DataVersity and CFO University. Apart from his consulting and advisory pursuits, he has trained over 4,000 professionals worldwide in Data…