Copy of Wading through Data Misinterpretation by tron.

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Slide Notes

Copy of Wading through Data Misinterpretation

Big data and data analytics are challenging for many reasons. Data misinterpretation can be the result. A quick few notes about data misinterpretation prepared for the CMO Mid Market gathering hosted in St. Louis by the IQPC in August, 2015.

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PRESENTATION OUTLINE

Wading through Data Misinterpretation

Photo by The Nick Page

Tron Jordheim

CMO StorageMart

Photo by Ochre Jelly

Data data everywhere

What meaning does it have?

Photo by BobMical

InformationWeek

Lisa Morgan's article is the basis for this deck.

Photo by giulia.forsythe

Domain Expertise vs. Data Expertise

Which do you have? Which does the data reader have?

Photo by Ross Mayfield

Everything has an asterisk*

*ignore variables, anomalies, special circumstances, data limitations, etc. at your own peril

Photo by hjhipster

Aggregation spells danger

too broad or too narrow... and it turns to mush

Photo by bradlauster

Inferences are conditional

look before you leap

Photo by cactusmelba

Statistical Significance is Compelling

The wind blows even if you can't see it.

Photo by Robert S. Donovan

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Data Visualization can help catch what the numbers missed

Photo by the_digitalmonkey

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Correlation or Causation

one thing does not always lead to another

Photo by wwarby

12.

Explanation can clarify or confuse

Be a good story teller!

Photo by Official U.S. Navy Imagery

13.

Thank you to the following

Lisa Morgan, Informationweek
Ken Gilbert, U. Tenn
Carlos Abisambra, Vortice
Andrew Chrsitoper, Aimia
Laura Khoury, Blossom Growth

Photo by Yahoo Inc

14.

Tron Jordheim

@tronjordheim

Photo by Gage Skidmore

Slide Notes