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Data Quality, Governance and Visualization

Thursday, August 17 2017 - Thursday, August 17 2017
1:30 PM - 7:00 PM

Add to Calendar America/Los_Angeles Data Quality, Governance and Visualization Join us for an case study discussion on data quality and data governance at Illumina. After which, we will dig into data visualization with the presentation Moving Raw Data to Useful Information.  Biocom Institute is proud to partner with the DAMA San Diego chapter to bring you this event. Biocom false MM/DD/YYYY

The Alexandria
10996 Torreyana Road
San Diego, CA 92121
Registration Deadline:
Wednesday, August 16 2017
4:00 PM


Data Quality and Data Governance at Illumina

Data Visualization: Moving Raw Data to Useful Information



1:30 pm – Registration & Networking

2:00 pm - Greeting and Sponsor Introductions

2:15 pm – Illumina Data Quality and Data Governance Case Study; Ken Mudd & Sally McCormack

3:15 pm - Networking

3:30 pm - Data Visualization:  Moving from Raw Data to Useful Information; Michael Scofield

5:00 pm - Sponsor Giveaways

5:15 – 7:00 p.m - Happy Hour 



Data Quality and Data Governance at Illumina

 From this case study, attendees will learn:

·       The importance of a business-centric Data Governance structure and organization

·       How to establish your business and IT partnership

·       The value of Data Quality tools in the identification and cleansing of data

·       Why you should forget about traditional IT practices when establishing Data Governance and Data Quality programs


Data Visualization:  Moving from Raw Data to Useful Information

 Data Visualization uses graphic techniques to convert raw, tabular data into decision-able information.  This process supports two major functions; first is data analysis (or business analysis) to help you understand what is going in the data and the business it describes.  The second function is to communicate to executives and decision-makers what is happening in the business and its environment which they need to know for major strategic decisions and policy design.

We will review the data-to-information life cycle (the basic conversion of raw data to information) and some of the issues of consistency, definition, and normalization.  We will then review the five most common types of charts, and the important difference between categorical and linear dimensions.  Then, we can discuss how each chart is best and appropriately used for different kinds of data.  Particular emphasis will be given to the context of data points, both historical values, and the proper selection of peer data to make your own business behavior more meaningful.

Perhaps the highlight of the lecture is a “rogue’s gallery” of really bad charts (from some surprising sources).  We will look at each and discuss why it is bad, and how it can be improved.  This leads to a discussion of the imperatives of data visualization:  to be legible, understandable, relevant, and truthful.



Ken Mudd
Manager, Material Data Governance
Illumina, Inc

In his role, Ken has project-based functional responsibility over the data quality, master data management, and reporting aspects of the material data domain. Ken has over 10 years of master data management experience spanning multiple manufacturing companies. He has effectively managed top-performing teams in various data governance organizations with an emphasis in SAP.

Sally McCormack
Data Quality Competency Director
Datasource Consulting

As a subject matter expert, Sally provides leadership, management, vision, and technical direction to ensure effective data quality delivery strategies are met. Through technological training, best practice development, and defined processes, Sally provides the executive oversight required for a successful data quality consulting arm. She brings over 13 years of data integration, data quality, data warehousing, and business intelligence excellence. She has expertise in both architecting and implementing ETL and data quality solutions and has provided strategic and tactical leadership on numerous projects, implementing enterprise data warehouses and data quality programs in biotech/pharmaceutical and other industries. Sally is a Certified Business Intelligence Professional (CBIP) in Data Integration and Certified Business Intelligence Professional (CBIP) in Data Analysis and Design.

Michael Scofield is a semi-retired faculty member in Health Information Management at Loma Linda University, currently lecturing in their School of Nursing.  He is a frequent speaker and author in topics of data management, data quality, data visualization, and data warehousing.  He has spoken to professional audiences in over 27 states, Canada, Australia, and the U.K. 

His career experience includes government, manufacturing, finance, and software development.  Now retired, he still does pro bono data mining and data quality analysis for non-profit organizations.   His greatest interest currently is data visualization, data quality assessment, and using graphic techniques to reveal business and economic behavior. 


Liisa Bozinovic

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