“Two decades ago the folks who prepared our reports, graphs, and visualizations were ‘data analysts’ who knew how to extract data from relational data warehouses and run it through reporting and visualization tools like Crystal Reports. Ten years ago, predictive models were built by ‘predictive modelers’ who understood both the extraction and preparation of the data as well as the specialized predictive analytic tools like SAS and SPSS that allowed them to prepare predictive models. In the last few years, Gartner now declares that we need ‘data scientist’ who have all the above skills but also understand the complexities of the new NoSQL databases like Hadoop and can marry data from many sources and types together to produce useful and profitable predictive models. The requirement for broader and deeper skills is real and must factor into any business decision to build in-house capacity, as well as vetting potential consultants.” William Vorhies ( August 19, 2014 )