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.
Webinar Objectives
- Define Data Quality
- Understand the key data quality dimensions
- Identify Common Misconceptions About Data Quality
- Understand the Impact of Misconceptions on Business
- Learn Best Practices to Improve Data Quality
- Case Studies and Success Stories for Data quality Improvement
Webinar Agenda
- Introduction to Data Quality (5 minutes)
- Data Quality Dimensions (5 Minutes)
- Myth 1 and its corresponding reality (5 minutes)
- Myth 2 and its corresponding reality (5 minutes)
- Myth 3 and its corresponding reality (5 minutes)
- Strategies and Best Practices for Overcoming Misconceptions (15 Minutes)
- Interactive Q&A Session (15 minutes)
- Conclusion and Next Steps (5 minutes)
Webinar Highlights
- 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
Who Should Attend?
- Data Analysts
- Data Governance Analysts
- Data Governance Managers
- Data Scientists
- Data Engineers