Running your business and analyzing results with accurate and consistent data is mission critical, yet most organizations struggle with bad data. An IBM study estimates that $3.1 Trillion of America’s GDP is lost due to bad data and 1 in 3 business leaders don’t trust their own data.
With data volumes doubling every two years, it’s becoming harder and more expensive to separate bad data from the good data. As such, data governance needs to be a top priority for improving data quality and driving data management across the enterprise.
- Understanding the three pillars of data governance: business rules, governance processes, audit & control
- How to develop and deploy a high quality data foundation for analytics in 90 days or less with Dynamic Information Warehouse (DIW)
- Leveraging business modeling capability and software automation to respond to business change in hours vs. months
- How to drive more value from data for corporate performance insights, operational management and regulatory compliance
- Demonstration of MDM modules in action with customer case studies including Anheuser-Busch InBev, Comcast, Royal Mail and others
The combination of business information modeling, DWA and MDM is helping today’s data-driven businesses eliminate manual tasks, reduce project risks and leads to improved data quality.
What data challenges are you facing? Is your organization equipped to uncover real, actionable insights to better inform the business?