Best of Upside's Data Digest
Articles explore the use of edge analytics, eliminating bias in big data, predictive models, data leaks, data lakes, and best practices for moving to the cloud.
- By Quint Turner
- September 15, 2016
The Many Uses of Edge Analytics
Edge analytics is when a connected device can analyze data as it is collected, before sending any data to the data center. As this article explains, this process improves efficiency by bringing real-time decisions closer to the data.
Eliminating Casual Bias in Big Data
The human brain has a tendency to find patterns, even ones that do not actually exist. This article focuses on eliminating hidden biases from all forms of data analysis.
Best Predictive Models Combine Lots of Data
(Source: The Conversation)
Many publications are using predictive analytics to forecast the 2016 election results. This article explains the development of an evidence-based model for predicting an election, and the perspective is applicable for building a predictive model of any kind.
Prevent Data Leaks from Departing Employees
Those who have just left your enterprise might leave with more than you realize. This article provides 8 best practices for preventing accidental theft of data by former employees.
Why Be a Skeptic About Data Lakes?
This article argues that data lakes have significant drawbacks -- that they encourage enterprises to store unneeded data and to store it haphazardly, exposing them to latency issues and regulatory risk.
Best Practices for Moving to the Cloud
(Source: Business 2 Community)
Shifting operations to the cloud is trendy, but you should make sure you will benefit from the migration. This article explains how to prepare your enterprise for such a move.
Marketing to High-Growth Consumers with Data (http://bit.ly/2bSoCax)
This article explains in three basic steps how marketers can find and target specific groups of high-growth consumers using big data.
Big Data's Impact on Decision Making
(Source: Harvard Business Review)
Clarifying who gets access and control of data -- and who can make decisions based on that data -- requires a plan, and this article examines how those plans are changing as big data has gotten bigger.
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.