Data science sophistication will increase
2015 is the year data scientists will become a mainstream career choice. Most universities are already offering courseware in data science in preparation of the dramatic rise of this new profession. Already high demand for data scientists, will snowball in the coming year, with nearly every enterprise having data scientists doing more than just studying customer behaviour heralded so much in 2014, but expanding into new areas such as data forensics to combat rising cyber threats, and the creation of new types of businesses based on data services. Data science adoption will be driven by the business and its requirements which will lead to an explosion of new tools and services focused on specific industries and departmental needs. In addition, the gap between expectations and reality will increase in 2015. Because many technologies are still very immature, newly hired data scientists are often very inexperienced regarding business questions and face the challenge of bridging the gap between business departments' operational needs and the capabilities of the technical infrastructure which is getting more and more complex.
The Gap between expectations and fulfilment of data scientists will get bigger
Data science as the science of "optimising your business by exploring/mining data" is becoming a mega trend, but there is a lot of confusion in the market. Regarding the job of data scientists, many big companies have already hired complete data science labs without any clear strategy. The role of a data scientist has to evolve next year by becoming a kind of human interface between "data business incubators" and the actual business departments who need to gain competitive advantages over their competitors. In 2015, the need for additional human resources in that area will accelerate, but the number of skilled people to fulfill these requirements cannot be satisfied. Therefore the gap between expectations and fulfilment will open even more.
Aaron Auld, CEO, EXASOL
Hadoop will improve data mining efficiency
A huge part of Hadoop projects are not successful, nor lead to any real business applications. But Hadoop systems are very agile, cost-effective, self-service systems for data storage allowing new types of data to be quickly stored and processed. Today this is the...