T4 EDW Tutorial: Data Fundamentals for Business

Time: Monday, March 27th, 11.30am – 2:30pm Pacific Time (PST)/2:30pm – 5:30pm Eastern Time (EST)

This Enterprise Data World (EDW) Digital Tutorial can be purchased on the official conference website, but the live tutorial will occur within the DATAVERSITY Training Center. You will receive your unique login credentials and confirmation once you've registered for this paid Tutorial at: https://edw2023digital.dataversity.net/registration-welcome.cfm

Registration for this Tutorial will also give you access to all active tutorials within the same time slot.

All paid Tutorial registrations include access to the free 2-day program Tuesday-Wednesday. Please note that you will receive separate login instructions for the free program, as it will take place on a different platform than the Tutorials. See your registration confirmation for details.  

The EDW Digital Conference site can be found at: https://edw2023digital.dataversity.net/index.cfm

Tutorial Description

Anytime you buy data, store data digitally, extract data, and/or mine the data for meaning and insights, you need to know the basics of data structure and quality…a kind of Data Literacy. You need to understand how to use the data, and what is and is not good for. 

This entry-level workshop will survey the basic concepts of data management and usage. A critical skill is understanding what can go wrong with data, and thus testing the quality of the data (and your understanding of its meaning) before you draw important conclusions from the data, and/or present your findings to decision-makers. 

Attendees will learn:

• The basic physical and logical data structures commonly used
• The difference between raw data (facts) and useful information
• Some common points of failure in data quality
• The importance and characteristics of good data documentation
• Principles of good expression of data for clarity and understanding

Speaker: Michael Scofield

Michael Scofield, MBA, is an Assistant Professor at Loma Linda University School of Nursing. He is a frequent speaker and author on the topics of Data Management, Data Quality, data visualization, and data warehousing. He has spoken in over 27 states, Canada, Australia, and the U.K. His articles appear in a variety of professional journals in Data Management.

Michael's career experience includes government, manufacturing, finance, and software development. Now semi-retired, he still does pro-bono data mining and data quality analysis for nonprofit organizations. He also guest-lectures at a number of colleges and universities.

His greatest interest currently is data visualization, Data Quality assessment, and using graphic techniques to reveal business and economic behavior.