Data Science Vs Data Science Technology

Data Science is about understanding the story the data tells us. It requires solid knowledge about fundamental statistics to begin with, a problem-solving mindset, lots of experience, and ability to use Data Science Technology. At a higher order, it requires ability to find solutions to real life problems with Data Science.

Data Science Technology enables us to work with volumes of data very efficiently. It includes working with large datasets, working knowledge in python, R, SAS, or SPSS, and visualization tools available in BI tools such as Power BI or Tableau or such.  Further to that, if one is keen on machine learning or artificial intelligence engineering, fundamental programming skills in C or Java like languages are essential. Or if one has to specialize only in data management like Big Data, relevant skills are needed.

If you have not assimilated yet, Data Science Technology is a sub-set of Data Science. Technology and tools exist to bring to life the mind of a Data Scientist. The thinking has to emanate from deeper understanding of the statistical math, problem at hand, and such higher order skills.

However, there is a predominant emphasis on Data Science Tech which does not solve any problem by itself. Understandably so because it is the easier part to teach. Anyone can pickup a piece of python code, or get a certification on a statistical package like SAS, or learn Tableau. But these skills can only make someone to be able to help a Data Scientist, who is rather solving problems, formulating solution and making valuable contributions to an organization. Data Science Tech is subservient to Data Science.

On the other hand, learning Data Science is harder and has to happen over a period of time. One doesn’t learn Math in a 2-month certification course. It is built over time.

But for an aspiring Data Scientist, it is not all lost. There is a little bit of mathematical foundation, logical reasoning, problem solving ability ingrained through many of formal education. If one can mine the dormant knowledge and enhance it, we will have a real Data Scientist for the taking.

VKademy aspires to train in Data Science, though it is harder than training in Data Science Tech. It may take a little longer, involve hard work for the learners, but will be extremely rewarding in the long run. These skills do not get outdated like software tools – like Python replacing R, R replacing SAS, SAS replacing SPSS and so on. Even AWS replacing Blue Mix, or Tableau taking a cut away from Power BI also. Technical skills are easiest to learn. What is more valuable will be harder. But we are here to help!