November 2017: Good Data, Bad Info

Presented by Michael Scofield, M.B.A.

Assistant Professor, Loma Linda University

Producing decision-able information from lots of raw data often requires complex processes which must be carefully designed and architected.

This presentation looks at the gap between raw data and decision-able information. Most of the chatter about data quality focuses upon raw, granular data describing discrete events and entities inside the enterprise and around it. But for data warehouses and decision-support, data must be converted into useful information meaningful to the decision-maker.

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September 2017: Cartographic License and Building Maps That Work

Presented by Sarah Battersby

Senior Research Scientist at Tableau Software

UPDATED: A PDF of the presentation is available for download

We live in a data rich world and many of the data that we encounter have a geographic link, such as a point coordinate, an address, a state, or country name.  Maps are a key part of understanding geographically linked data and utilizing it in decision making.  In designing maps, virtually anyone with a computer and an internet connection can be a cartographer – regardless of knowledge of principles of spatial data or visual and cartographic communication best practices.  The good news about this democratization of cartography is that everyone is empowered to explore their own data with maps.  The bad news is that anyone can make a map.  While many map authoring tools help guide the design, it is still easy to unintentionally (or occasionally intentionally) mislead readers.  The variant of the truth that we find in maps is largely driven by choices that the cartographer makes in the data collection, cleaning, analysis, and visualization process.  In this presentation I consider issues of how the map designer and reader perceive mapped data and where “noise” can creep into the communication to distort the intended message.

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July 2017: Data Science, Predictive Analytics

Presented by Dean Abbott

Chief Data Scientist, SmarterHQ

UPDATED: A PDF of the presentation is available for download

Most of what data scientists do is nothing new, and much of what’s new is really a throwback to what we used to do 20 years ago. So why data science so popular now? In this talk, Dean will describe what differentiates data science from related fields like Business Intelligence, Predictive Analytics, and Statistics, and will illustrate the use of data science from case studies in customer analytics and fraud detection.

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