By using website you agree to our use of cookies as described in our cookie policy. Learn More

TDWI Upside - Where Data Means Business

Data Digest: Preventing Data Leaks, Biased Models, and Poor Predictions

How to stop employees from leaving with enterprise data, avoid seeing causal connections that aren’t there, and create better predictive models by combining diverse data.

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.

Read more at CSO

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.

Read more at Datanami

Best Predictive Models Combine Lots of Data

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.

Read more at The Conversation

About the Author

Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at

TDWI Membership

Accelerate Your Projects,
and Your Career

TDWI Members have access to exclusive research reports, publications, communities and training.

Individual, Student, and Team memberships available.