The BI industry carefully monitors business trends on a year to year basis. Majority of these trends are largely influenced by data production and the use of corporate data to gain a competitive advantage. Meta-trends also influence the BI market. These Meta trends are: Digitalization, Consumerization, Agility, Security, Analytics, Cloud, Mobile, and Artificial Intelligence.

A recent study report by Gartner finds four trends that will drive the evolution of BI and analytics over the next few years. The first is a shift from mere reporting to analysis of Big Data streams. The second is the fast-growing role of connected "smart" devices in providing the data streams that BI works with. The third is the merging of traditional vended BI software with hosted solutions in the cloud. Finally, the fourth trend will be the mainstreaming of BI and analytics over the next few years.

Lack of good, consistent quality data is cited as the number one challenge organizations face to realizing the full potential from analytics (A.T. Kearney’s “2015 LEAP Study - Leadership Excellence in Analytic Practice”). Excessive time and resources are needed to manipulate and “roll-up” data before business analysts can start to use it for reports, analytics and insights.

According to a recent press release, “Litmus Health, a clinical data science platform focused on health-related quality of life, today launched into public beta. The company uses data collected at the point of experience from wearables, smart devices, and home sensors to inform clinical endpoints and guide trial management. Litmus is initially focused on Phase I/II clinical trials. The decision faced by pharma to move forward from Phase II to Phase III is an expensive one, as several hundred million dollars usually hang in the balance.

AN AUSTRALIAN led Silicon Valley venture has been valued at $A1.9 billion, although no one knows exactly what the company does.

Co-founded by Victorian expat Tim Kentley-Klay, the mysterious start-up called Zoox has remained in stealth mode for the two years it has been in operation.

Few things in technology outside of catching Pikachu on your iPhone have been hyped as much as big data. However, with any trending topic, new technology or invention that’s being called the “wave of the future,” it’s important to look past the hype and analyze what’s actually going on. Outside of widespread media attention and the increasing importance placed on collecting data, big data is rarely used.

Profile 1: Ram Narasimhan at GE

In What Data Scientists Do All Day at Work, the interview between Wall Street Journal’s Deborah Gage and GE’s Ram Narasimhan bares it all. Although Mr. Narasimhan left an airline business to join GE in the Bay Area, his background in industrial engineering and PhD work, coupled with extensive experience managing airlines assets positioned him as an expert data solver and predictor at GE. He tells Deborah Gage that his job in GE as Data Scientist is quite different from an average Data Science job and that he spends most of his time maintaining assets in GE plants.

The worldwide demand for qualified Data Scientists continues to grow and one of the most common queries in many an industry insider’s mind is so, what is it that a Data Scientist does? When lay persons within an industry try to grasp the essence of a Data Scientist’s life, the confusion that boggles everyone is that this unique profession cannot be linked to one particular trade, one particular academic degree, or a single organizational role. Rather, the Data Scientist’s role is to identify and solve day-to-day business problems through a multi-disciplinary approach that encompasses many different skills like mathematics, statistics, computer science, operational research, and of course, business.