A common misconception about Big Data is that it is a black box: you load data and magically gain insight. This is not the case. As this New York Times article “For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights” describes, loading a big data platform with quality data with enough structure to deliver value is a lot of work. Data scientist spend a comparatively large amount of time in the data preparation phase of a project. Whether you call it data wrangling, data munging, or data janitor work, the Times article estimates 50%-80% of a data scientists’ time is spent on data preparation. We agree.

Source: www.datasciencecentral.com

Big data requires lots of prep! 

Engineers at Sapphire Now discussed the potential and limitations for SAP S/4HANA as a platform for managing an enterprise Internet of Things and the big data that strategy requires.

Source: www.informationweek.com

I’ve written before about my own passion for futbol and how it was a powerful force in my youth growing up in Colombia. For me, as it is for sports fans the world over, the true power and relevance of sport is the community it creates.

Source: blogs.microsoft.com

This is a great insight you should read this if you are in the mobile space.

If you’re not yet using big data and analytics to do your job, you likely will be soon, says Powerlytics’ Kevin Sheetz.

Source: www.ibamag.com

great post by a great colleague