Tony Cosentino of SmartDataCollective.com writes, "Big data analytics is being offered as the key to addressing a wide array of management and operational needs across business and IT. But the label “big data analytics” is used in a variety of ways, confusing people about its usefulness and value and about how best to implement to drive business value. The uncertainty this causes poses a challenge for organizations that want to take advantage of big data in order to gain competitive advantage, comply with regulations, manage risk and improve profitability."
Big Data Analytics for Dummies is a valuable resource that addresses the practical dilemmas surrounding Big Data and provides a step-by-step approach on how to sidestep common pitfalls, including:
- How do you give Big Data the right context so that it isn't stuck in isolation?
- Who can create the analytics you need to make the most of Big Data's potential?
- What do you need to do to make Big Data usable by decision makers on my team - TODAY?
The yhat blog lists 10 R packages they wish they'd known about earlier. Drew Conway calls them "10 reasons to always start your analysis in R". They're all very useful R packages that every data scientist should be aware of. They are:
Vincent Granville was formerly Chief Data Science Officer at Authenticlick. Most recently, he successfully launched AnalyticBridge, the largest social network for analytic professionals, with 45,000 subscribers. Vincent is a former post-doctorate of Cambridge University and the National Institute of Statistical Sciences. He was among the finalists at the Wharton School Business Plan Competition and at the Belgian Mathematical Olympiads. In this piece if offers 66 mostly open-ended questions, to assess the technical horizontal knowledge of a senior candidate at a high level.
We'll this is basically an infomercial for Alteryx analytics platform, but its good content. I like the way they explain Big Data and how their solution fits. Enjoy!