Is Data-Scientist the profession of the future?

Over the last two years, ninety percent of all saved data has been generated worldwide. And we can do something with all that data. For example, if your company knows where, how and how often customers use an app, the app can be optimized and better respond to the needs of the user. Due to this wave of Big data, a new profession has emerged. According to experts, data scientist is the profession of the future.

With every new and trendy profession, a proliferation of job names emerges. Of course, we know the software developers who called themselves architects in the past, while they were not. Thus, a business analyst is also not equal to a data scientist.

What is a Data-scientist?

First of all, modern technologies have no secrets for a data scientist. As a data scientist you are used to finding, extracting, transporting, editing and visualizing relevant data. This means that there must be specific knowledge of the most widely used programs, programming languages ​​and techniques in the field.

Secondly, a data scientist can translate the collected data to gain value for the organization. The promise of big data – where the data scientist has its function – is that, from large amounts of data, valuable relationships are distilled that will enable the business to grow. Finally, you can expect a data scientist to develop concrete ideas for the organization based on these insights.

Technical knowledge alone is no longer sufficient for a data scientist. He will also need domain knowledge and a lot of creativity, curiosity and inventiveness. Or as Steve Jobs said in his inspiring speech at Stanford University in 2005, “Stay Hungry. Stay Foolish”.

Sufficient Mandate

Organizations must ensure that the data scientist has sufficient mandate within the organization to get business together. If that is not the case, initiatives will never be more than initiatives and organizations will not benefit from their big data. Give a data scientist the space to establish something. Then he or she can really create value from data.

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