How to Calculate Data Confidence
Research Analyst, Enterprise Data Management
Nathaniel Rowe is a Research Analyst in the Enterprise Data Management practice at Aberdeen Group. His practice focuses on the rapidly growing volume of business data, and the Best-in-Class practices for the creation, capture, management and analysis of this information. His research topics cover the high performance hardware and software needed to handle data at scale, and developing technology related to distributed computing, mobile technology, social media and clickstream data, unstructured data, and physical documents. His recent reports have benchmarked strategies for Big Data, document management, master data management, digital media and Business Intelligence.
Nathaniel has worked at Aberdeen for over three years. Previously he spent several years in the electronic disaster recovery industry, and worked for Yale University’s Department of Digital Media and Dissemination.
Director, Product Marketing, InfoSphere
David Corrigan is director of product marketing for IBM's InfoSphere portfolio, which is focused on managing Trusted Information. His primary role is driving the messaging and strategy for the portfolio of information integration, data quality, master data management, data lifecycle management, and data privacy and security capabilities. Prior to his current role, David has led the product management and product marketing teams for Master Data Management (MDM), and has worked in the Information Management space for over 14 years. David holds an MBA from York University's Schulich School of Business, and an undergraduate degree from the University of Toronto. Follow David on Twitter @dcorrigan.
Data confidence is an abstract notion in most organizations. Yet it is critical in order to make your front line workers trust and act upon big data and analytic insight, as even the most game-changing analytics will have no impact if your team doesn't use them, because they don't trust in the data or the insights
Attend this webinar to learn how to:
- Calculate data confidence and improve the adoption of big data & analytics
- Utilize data confidence scores to align resources to new big data & analytics projects
- Calculate and share data confidence in your big data projects
Register for this webinar to learn about compelling new research that identifies the critical criteria to measure and score confidence levels in customer data to make better business decisions. You will also learn about a new online tool that provides a fast and easy way for attendees to obtain their score.
BONUS: Attendees of this webcast will receive a complimentary copy of The Information Confidence Calculator: Measuring Trust in Data report.