Data Digest: Tacking Bad Data, Smart Algorithms for Prescriptive Analytics, and Achieving a Better BI ROI
Articles offer tips for reducing data clean-up time, how bad algorithms lead to "bad" data, and how to improve your ROI on BI.
- By Quint Turner
- January 12, 2016
How to Prevent Bad Data from Bogging Your Team Down
(Source: Datanami)
Bad data can happen to anyone, but data itself is not inherently bad. Rather, inconsistent data quality forces data scientists and analysts to spend up to 90 percent of their time cleaning bad data. This article has tips for improving this statistic and getting analysts to work on analyzing rather than cleaning.
Prescriptive Analytics Requires Smart Algorithms to be Effective
(Source: Datamation)
Many enterprises have adopted prescriptive analytics, the way of using algorithms to analyze data and immediately take action, to avoid bad data quality. However, as this article argues, only good algorithms will lead to effective prescriptive analytics; a bad algorithm will only lead to “bad” data.
Achieving a Better ROI on BI
(Source: Database)
The ROI of data analytics and business intelligence is tricky to pin down, but according to recent studies, enterprises are raking in $13.01 for every dollar spent on business intelligence. This is an increase, but that number can go higher. This article has the scoop on improving your ROI on BI.
About the Author
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.