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Best of TDWI's Data Digest

Interesting articles we found on the Web focus on the pitfalls of predictive analytics, prepping big data, spatial analytics, storytelling, and simplifying visualization projects.

Avoiding Five Common Pitfalls of Predictive Analytics
(Source: I Crunch Data News)

Predictive analytics is seen as the future of BI, and for that reason there are many misconceptions about the implementation and use of predictive analytics. This article blows five common misbeliefs out of the water.

Solving the Prep Problem in Big Data
(Source: Datamation)

Up to 90 percent of a BI professional's work ends up being data preparation. This has not always been the case, but due to the paradigm of "collect data first, ask questions later," most data is thrown into a data lake without any thought. This article offers advice on shifting this paradigm to a more efficient method by suggesting changing the approach to data preparation.

Visualizing BI with Spatial Analytics
(Source: Information Age)

Data can come from anywhere. Nowadays, figuring out where that data comes from can be crucial for best exploiting what your enterprise collected. This article reviews spatial analytics, looks at a few case studies, and then extrapolates what spatial analytics might be good for in any enterprise.

Data Scientists Need to Be Storytellers
(Source: Harvard Business Review)

Data is made up of simple facts that anyone can collect. Coming to a conclusion based on data and being able to present that conclusion in a logical way is something only few can do. This article argues that the best data scientists tell stories from data and are good communicators first and foremost.

Making Sense of Big Data
(Source: Forbes)

The possibilities big data provides are staggering; so much so that it is hard to figure out where to start when analyzing it. This article offers eight basic tips for getting the most useful information out of big data.

Simplify Visualization Projects for Best Effect
(Source: Tech Target)

As collecting and analyzing big data gets easier, the presentation of the findings through data visualization is growing more important. Good data visualization presentations can communicate plenty of valuable information in an understandable manner. The key to making a good presentation, this article argues, is making the visualizations as simple as possible.

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

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