Data science has established itself as one of the most promising and fastest expanding fields of knowledge and scientific application. The internet has been lately overflowing with advertisements of data science jobs – a lot of which are not in fact data science jobs – and training institutes. Even if you have never really had a knack for the role of an analyst or a data scientist the internet humbles you with reasons why you should instantly quit your current pursuit; launch a career in data science, and look for a data job that lets you apply the newly acquired skills.
Data science or even data in itself is extremely powerful. It has the ability to impact your life and your business in so many different ways that confining its scope to a few job roles and designations seems ‘cute’, at best.
A general skill v/s a special skill
Let us say you are an entrepreneur who sells wooden artefacts. Would you say that all the math lessons that you had received in school were lost on you because you did not become a mathematician? Can a cab driver not use the basic concepts of geography in his way of life? Can a basketball player say that he should never have acquired language skills? No. That would be silly because these are general skills which help us go about our lives. I think, well, in fact a lot of able minds think that we may have arrived at a time when data science has to be treated as a general rather than a special skill.
What I mean is that data science training or analytics education should not be only for those who are eyeing a career as a data analyst, a data engineer or a data scientist. It can be for a marketing executive, an architect, an entrepreneur, a writer, a musician. Practically anyone who wants to tap into the enormous resource of data can benefit from data science training.
Data science as an umbrella
When we say data science training for everyone we do not really suggest that every person should invest his or her time and money in learning how to create machine learning algorithms and how to set up neural networks and how to code a programme that can differentiate asteroids from space junks, no. Data science is an umbrella term that includes a lot of different skills of different difficulty levels. If you are using pivot tables and filters to make sense of enterprise data on an excel spreadsheet, that is right there a practice in data science. So, the first thing that is needed is the awareness that data science is more than just a high-tech discipline practised only by the math professors and computer geeks.
Applied data science in different professions
Let us say you want to work as a marketing manager. You have excellent communication skills, you are good with words, and you know how to pitch an idea in front of a crowd of unfamiliar and uninterested people. If you acquire some data science skills, say you know how to use NoSQL or R to make sense of data, you will instantly become an asset.
If you are an entrepreneur who is willing to take the business online and fight against the well established corporations to build a niche. Your best shot is data analytics. If you know how to collect, clean, process and analyse data, you save a ton of money which you would otherwise be paying to an analytics services company to look after your data.
Say, you have started an edutech firm and want to stand out. You would need a good deal of data analytics to set the curriculum right. Same deal, you do it yourself and save a ton of money.
This list could go on. Whatever your field may be, data science training strengthens your footing in the industry.
Data centric ecosystem
Just like the natural ecosystem has air at its center the business ecosystem has data. Then again data can impact our relationship with nature as well, hence it would be unjust to call it a part just of the business ecosystem. A data centric approach in all quarters makes decisions more informed and executions more sustainable. So, no matter what you do a course of data science sas training, cannot harm you. A company that houses people with an awareness and some training of data science every job can be done better.
