Speaker: Garth Honhart of DesignMind

How do you address data quality? Should data be fixed, corrected or just left alone? If so, where? At the source? In the system of record?

In a typical scenario your team pulls data from the source systems, builds a cube, and releases it to the business. You think it's a job well done until the e-mails and calls asking why nothing seems to be working like the demos. The reason? - a data quality problem.

In this session, Garth will review several different scenarios that you can use to capture and correct (or expose) bad information.

You'll learn:

• Where data quality issues can manifest
  
• The multiple places data can be "fixed"
  
• How to address auditing
  
• How to enlist Data Stewards (subject matter experts)
  
• Different approaches to fixing bad data

Garth has hands-on BI experience in the semi-conductor equipment, regional freight delivery, enterprise software, healthcare, financial, commercial real estate, and medical device industries.