Data Scientist: Hype or Sexy?

Data Scientists seem to be everywhere nowadays. This title has seen a huge increase in appearences in job descriptions, as Indeed.com demostrates in its data.
There are several sites and articles that even describe the job as sexy:

The combination of handling Big Data and Analytics is what makes this title so attractive. So far handling data and analytics were too parts, sometimes combined in one person, but most times not. But with all the unstructured data available and new tools to handle it, the combination is easier to handle for one person. But technical understanding is not enough to become a Data Scientist. It requires an understanding of products and customer behaviour as well as how to manage and analyse data.
Right now there is no programm that graduates with the title Data Scientist, so companies have to look for people that learned all skills during their career so far or have strong affinities towards analysis or programming with corresponding skills learned during their studies or education.
Because of the interdisciplinary area of this field, some companies try to get their hands on graduated physicist. Their studies involve a great deal of interdisciplinary themes and the affinity to both algorithms and research.
Other possibilities are Business Intelligence Analysts, Data Mining specialists or even Web Analytics manager, depending on their career so far, especially their experience with different kinds of data and their presentation skills regarding actions resulting from their analysis.
All in all this new title and the news coverage it is getting is a great opportunity for people already working in this field and newbies wanting to work with both data and analysis.

This makes this new profession sexy.

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Data Science: What is it?

Data Science is an interdisciplinary field of sciences. It includes:

      Data Engineering
      Math
      Statistics
      Advanced Computing
      Visualization
      Domain Expertise

It revolves around, as the name suggests, working with data. With the development in creating big sets of data in our society, the need for analyzing this data grows across all industries. And this calls for people, who can work with data, analyze it and make their findings available for management decisions. Here comes into play math, statistics, expertise and visualization.
One of the most important challenges is, to integrate findings from unstructured data, like logfiles, and structured data, like databases. This enables a company to develop a whole new view of their customers and their products.
One task of data science is to make all necessary information available and filter out the noise that this information age provides us with. This is where statistics and data mining come into play. Finding effective ways to distribute these findings is partly data engineering, math and visualization. Presenting results from analysing data in graphical form is a way to make it easier to grasp the results.

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