The data scientist focuses their efforts on developing analytics solutions that solve a specific and unique business problem. The primary reason for this declining demand, according to the author was that increased automation and operationalization of business processes will not require the technical skills of the data scientist. IT individuals steeped in the more traditional computer science discipline are trained and developed to focus their skills on developing solution that streamline business processes. Creating a technological environment which allows access to data and the potential for increased automation is the role of IT. This kind of scenario is simply going to increase the demand for both data scientists and IT in our Big Data world, regardless of certain opinions on the declining importance of data science. .Read more at: https://www.smartdatacollective.com/demise-data-scientist-heresy-or-fact/

Google released the Dashboard Analytics Solutions Gallery more than a year ago, but marketers are yet to take full advantage of this free resource. Most advanced Google Analytics users have created custom dashboards but few have imported templates from the Solutions Gallery.This reluctance is caused by unavailability of proper support stuff, limited usage process information &preference of custom made solutions etc. However, Google Analytics Solutions Gallerydashboards can be used to find insights and drive more profit.To use it as your advantage, the following steps can be followed:

·         1^st: Decide about what insights you are actually looking for.

·         2^nd: Create new Dashboard & import from Gallery.

·         3^rd:Filter Gallery results by Popularity, Reviews, Category or Type.

·         4^th: View Data, look for insights, & Automate Reporting.

·         5^th: Edit, Customize or Segment Data as required.

To read more, visit the following link:

http://searchenginewatch.com/article/2341320/5-Steps-to-Quick-Insights-Using-Google-Analytics-Solutions-Gallery

Big data is the buzzword and messenger, but not the whole story. Yes, tons of telecom use cases will fit the so-called 3 V’s of big data: volume, velocity of analysis and variety of technologies. But today, a rise of fourth V can be observed in the big data equation: Value, referring to optimizing performance, maximizing revenue & monetizing the telecom business in more sophisticated ways.

The Telecom Analytics & Big Data Market, a breakthrough analysis report by Dan Baker, editor of the Black Swan Telecom Journal & research director of Technology Research Institute, gives us new insights about telecom big data analysis. In an interview with Craig Galbraith, Mr. Baker speaks about competition, barriers of market entry, customer experience, network analytics, integration with cloud, outsourcing & big data.

Read more at...

http://www.billingworld.com/articles/2014/03/telecom-big-data-analyst-report-explores-solution.aspx