Data Scientists: Making Sense of Big Data

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12 Mar Data Scientists: Making Sense of Big Data

Currently, the data scientist has one key priority: explain the applications and benefits of Big Data to the enterprise. This article contains insights from an HR consultant, an analyst, and a researcher on the challenge of grasping the fundamentals of Big Data and communicating them to the organization.

It’s like a roll-call of the biggest names in German business: transportation and logistics specialist Deutsche Post, world-leading reinsurance company Munich Re, and telecommunications giant Deutsche Telekom are all advertising the post of “data scientist” on online employment websites such as stepstone.de and monster.de.

SAP is also on the look-out for experts to join a predictive analytics team in Dublin, whose core task will be to develop forecast models and algorithms based on SAP HANA, to identify markets for them, and to communicate their findings to co-workers who do not have a technical background.

Big Data training: “Empowering employees to communicate”

Currently, there is still a genuine lack of understanding about the added value that Big Data can bring to the enterprise. As a result, Michael Mock from the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS) helped initiate a training program in 2013 that aims to highlight the opportunities that Big Data can offer. He reports that most of those who sign up for the training program use it “to gain a basic knowledge of the applications and benefits of Big Data and to acquire the practical knowledge they need to run Big Data analyses in their own enterprises.”

In other words, companies send their employees on these courses to find out more about how Big Data really works. The multi-faceted training modules are offered at regular intervals and cover topics such as the strategic significance of data analysis, the underlying architecture it requires, and how to handle massive volumes of data (or Big Data).