I am sure you have heard this before that data is the new oil. Data is used by governments to provide better services to its citizens. The private sector is already using it for product analysis, consumer behavior, patterns and insights that help uncover details that make a company more efficient and targeted.
What is data science ?
Data Science, if you take it literally you are in the right direction. It refers to Science of data. To put it in layman terms it is scientific study of data. Now, this would involve statistics and math. Data is voluminous and Gargantuan. Hence we need statistics to cut short and make sense of it.
The word data science has been there around half a century. In past 7 years, it has gained much popularity owing to shift in business process and sophistication. Too late to say but the world has gone digital. We leave our digital footprint everywhere we go. Everything we do on digital landscape gets recorded somewhere in digitally.
Mountains of data are stored in servers located somewhere. The data is collected and processed to discover patterns which is called data mining. Data Science goes many steps ahead and uses Mining, Predictive Visualization, AI (artificial intelligence), Visualization, Math and Statistics.
Components of data science
Ideally, a Data Scientist should be good when it comes to being analytical.
- They should be good with numbers, computer science and statistics.
- Data Scientists are essentially problem solvers of any business organisation.
- They offer insights and solutions to company to make it profitable or cost effective. (How, you may wonder but that’s later in the article)
Much of the work of Data scientist is that of a researcher. Therefore a data scientist would take input in the form issues/problems of an organisation and collect data both in structured and unstructured form. However, collecting data in unstructured form poses a challenge. The unstructured data is any data which is induced through us (humans) for example it can be our comments on social media to our online shopping behavior.
A diagrammatic representation of components :
It is divided into various levels where input is categorized as taking a problem and designing a hypothesis. The next level involves collecting data which graduates to upper level increasing the role analysis and research. A diagram below shows requirement and level of sophistication when it comes to Data science.
As you can see that data scientist work conforms to Analytics and Testing/experimentation. For structuring ‘data’ engineers are required. Obviously these data engineers are computer science/IT engineers. Notice that machine learning and AI are performed ML engineers and Research scientists. Most importantly, this forms the pyramid of data science.
A career here is very effective in terms of being a fruitful career option. In context of India in terms of demand there are not many who have this skill or certification. Hence, Data Science’s prospects shines brightest as whole world has gone digital and is increasingly becoming automated. Consequently increasing dominance of computer science and data enormously.
Data Science as highlighted by Mckinsey’s report had outlined Deficit in Data Analyst jobs pointing towards a demand in 2011. WEF(World Economic Forum) mentions it as dominant career in its Future of Jobs report 2018. Naturally then a career in data science is set to be a hot career of the future.
For a detailed or comprehensive understanding refer this