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Data Scientists: Making Sense of Big Data

March 11, 2015 by Andreas Schmitz

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).

Michael Mock from the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS) sums up the goal of the training program as "empowering people to communicate about big data".

Michael Mock from the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS) sums up the goal of the training program as “empowering people to communicate about big data”.

An innovation potential analysis of Big Data performed by the Fraunhofer Institute on behalf of the German Federal Ministry for Economic Affairs and Energy (BMWi) revealed back in 2012 that, while more than 80% of those surveyed could see the relevance of Big Data growing, they felt the need for “help in implementing and executing Big Data strategies in their companies,” says Mock.

According to the study, companies associate Big Data with a whole host of practical scenarios, including personalized product offers, sales forecasting for planning and control, monitoring markets for sales opportunities, predictive maintenance, and fraud detection for the financial industry.

“These findings were the trigger for us to develop our training offering – in the true spirit of technology transfer,” says Fraunhofer researcher Mock. In his experience, the majority of participants are analysts, IT personnel, and business developers. As mentioned already, the key goal of the training program is to “empower people to communicate about Big Data.”

And, with Big Data now featuring prominently on the academic agenda right across the European Union, researchers from the Fraunhofer IAIS are busy working with eight other research institutions and universities to develop a pan-European data science curriculum.

Big Bata: Red-hot topic for recruiters

As well as possessing the necessary technological savvy to perform traditional data analysis tasks, data scientists also need to be creative in implementing and analyzing business models. This combination of technical expertise and business acumen is what sets the data scientist apart from his or her fellow specialists in IT.

According to Gartner analyst Alexander Linden, a data scientist must possess the knack of being able to “identify business value from mathematical models.” But that vital business value can only materialize if the data scientist also networks with other departments, understands their objectives, is familiar with their data and processes – and can spot the analysis options they provide.”

The challenge for HR officers and HR consultants, says Gartner, is to find talented people who have both in-depth technical knowledge – about data integration and preparation, computer and database architectures, and data mining – and the ability to develop intelligent algorithms. But that’s still not enough, says Markus Krahforst. A senior consultant in the Best Practice Group Technology at Kienbaum Executive Consultants, Krahforst fills expert and management positions for IT companies and telecos. “Big Data has been a red-hot topic for us since 2010, he says.

He has recently filled 10 open positions, the successful candidates commanding salaries of between €80,000 and €150,000. What companies are looking for right now are marketing and sales managers, that is, managers who are equipped to handle business topics, rather than those with purely technological expertise. And they don’t necessarily have to have “data scientist” written on their business cards either. Data visualists, senior consultants, principals, and managing directors are also familiar with Big Data topics.

At the end of the day, the important point is that the successful job candidates should have a fundamental understanding of Big Data’s relevance to the business. Ideally, they will not only have an academic background, but also relevant experience in scientific subjects such as mathematics, physics, or information technology, and will already have worked in a data science role. Their “structured, scientific approach” is what makes them stand out from the crowd.

For Kienbaum, there’s one essential criterion: “A data scientist must be able to tell a salesperson what a product can do and what the potential variants are.”

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