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Working with Dirty Data: To Cleanse or Not to Cleanse... and How to Decide

Nicholas Marko and Oleg Roderick address the issue of using incomplete, damaged, incorrectly interpreted, and otherwise “dirty” data in modern analytics, and use their experiences in healthcare as a baseline from which to discuss this universal challenge in data science.

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Channels: Wolfram Data Summit 2015

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20 videos match your search.
Stephen Wolfram Data Summit Opening Keynote Part 151:12
Stephen Wolfram Data Summit Opening Keynote Part 230:40
A Brief Address by Conrad Wolfram7:13
Working with Dirty Data: To Cleanse or Not to Cleanse... and How to Decide25:31
Scientific Data, Privacy22:25
Big Brother vs. Big Data: Privacy-Preserving Threat Analytics at Scale22:00
Using Big Data to Predict Online Trends21:41
Data Science for Data-Driven Application Systems in the Internet of Things35:26
Protecting Consumers of Financial Products and Services26:46
Bidding Strategies for Display Advertising: How to Avoid Boiling the Ocean22:34
Data is the Only Marketplace21:34
Open Data Science: Leveraging Public Data to Explore Urban Life24:05
Data as Code/Code as Data21:05
The Webdata Blindspot: How Data-Driven Companies Are Missing Out on the Internet14:05
Building and Linking the Public Goods of the 21st Century25:33
Data Sleuth: Detecting and Recovering Missing Data in International Trade Networks13:57
Prospecting for Habitable Planets25:03
Quantifying, Visualizing, and Forecasting Global Human Society: What It Looks Like to Compute on the Entire Planet21:17
2016 Election Media as Data 18:06
Inconvenient Truths: What Do We Know, How Do We Know It, and How Do We Know We Know It?29:23