Business, IT, and Self-Service Data Preparation: Can We Talk?
TDWI Speaker: David Stodder, TDWI Research Director
Date: Thursday, September 29, 2016
Time: 9:00 a.m. PT, 12:00 p.m. ET
Webinar Abstract
One of the hottest trends today is self-service data preparation. Following the path of front-end tools for self-service business intelligence (BI) and visual analytics, self-service data preparation is aimed at providing nontechnical business users with the ability to explore data and choose data sets to fit their BI and analytics requirements. The goal is to reduce IT hand-holding—an ambitious one considering that, according to TDWI research, in most organizations IT manages nearly all data preparation steps, which can include data ingestion and collection, data transformation, data quality improvement, and data integration. Self-service data preparation thus represents a significant and potentially destabilizing change for IT and the way that IT and business work together.
How will IT govern and secure data assets, including how the data is used and shared? Who will be responsible for data stewardship and making sure that data quality is appropriate for BI and analytics? In addition, if each user or department is preparing their own data, what happens to the concept of shared data services? Will the “single truth” be lost amid the silos?
Clearly, there are thorny issues to resolve. Self-service is here to stay. Join this TDWI Webinar to find out what self-service data preparation means for IT governance and management of data assets. Business and IT leadership must communicate and develop a joint strategy to avoid pitfalls and ensure user satisfaction. As comedian Joan Rivers would have put it, “Can we talk?”
In this Webinar, you will learn:
- What self-service data preparation is, and what the trend means for IT data governance and management
- Potential pitfalls of self-service data preparation and how business and IT can overcome them
- Keeping eyes on the prize: how business and IT can work together to improve data for BI and analytics
David Stodder