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Lunchalytics

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Daniel H.
Lunchalytics

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Analytics is the use of data and analysis to improve the performance of an organization. In other words, it's the search for a free lunch. Ergo, we combine compelling speakers with a free lunch.

The format: Five speakers, five minutes each, 3 bullets max (If you can't kill it with three bullets, you can't kill it).

Speakers for this month:

Rhys Chouinard
Corporate and Economic Analyst, City of St. Albert
Topic: The Power of Pointing at Graphs: Leveraging Different Visualizations for Analytics-Driven Insight Discovery
Abstract: Humans are nature’s most powerful pattern recognition tools. When analysing data, it’s important to visualize the information in such a way that the pattern can emerge and be quantified. This presentation will showcase 6 or 7 different visualizations, to help us answer questions such as: Are we really in “oil country”? How has St. Albert’s age profile changed over the years? Where do people use twitter from the most? What drives people to move to a new community? And if time permits, we’ll take a peek into the world of dark matter detection, and see how visualizations can help you build tools to explore the limits of human understanding.

Fraser Gallop
Product Manager, LightHorse Innovation
Topic: Visualizing Performance on Construction Projects
Abstract: Effective collaboration is essential in modern construction projects. Streamlined communication helps to avoid costly delays and mistakes. Online collaboration tools can generate tons of data about construction projects, and have been for quite some time. More recently, we have new visualization tools that can help us see and understand this data.

Joey Cherdarchuk
Analytics & Data Visualization Consultant, ‎Darkhorse Analytics
Topic: Data Looks Better Naked: How to ensure your visuals are revealing
Abstract: Edward Tufte introduced the concept of data-ink in his 1983 classic The Visual Display of Quantitative Information. In it he states "Data-ink is the non-erasable core of the graphic, the non-redundant ink arranged in response to variation in the numbers represented" Tufte asserts that in displaying data we should remove all non-data-ink and redundant data-ink, within reason, to increase the data-ink-ratio and create a sound graphical design. Stephen Few convincingly argues that some redundancy is often more effective and we agree, however, most graphics don't struggle with understatement. In fact, most contain a stunning amount of excess ink (or pixels). Rather than dressing our data up we should be stripping it down.

Food starts at 1145, speakers start at high noon.

We hope to see you there.

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