What do we understand by ‘Data Science’?
While looking for a job in Data Science, there is one thing which is very crucial to understand – even though Data Science has been around for sometime but the jobs have been relatively new. So for any firm (barring the top 3 giants – Google, Amazon and Microsoft), you will find people who have worked in Data Science roles for a maximum of 3 years or they will have 3 years of relevant experience.
So no need to be scared about not having sufficient experience. What matters more is that how much you are willing to learn and how much you are willing to get your hands dirty with.
The second important thing to understand is – what is Data Science.
Since a few decades, there has been immense improvement in the storage mechanisms and as a result, the storages have become very easily and inexpensively available. Thus, we all have started storing a lot of data digitally. Some of the data were already being captured – like file systems at hospitals, which is now digital. Other data like flight records – on an average a flight generates a few GBs of data every second. Now all this data is of different kind. The easiest form of data is the one we can store in traditional relational databases – structured data. There is other like JSON, XML – which is semi structured data but can be easily read through programming languages. The final kind is images or videos – unstructured data. With the new changes in computer science, we can definitely deal with these as well but it is just still in the future to derive relations in these.
Since we have different kinds of data, we also have different streams or specializations in Data Science.
These are few of the main things in which people work and make a living.
Artificial Intelligence
Machine Learning
Deep Learning
Visual Analytics (Audio and Video)
Natural Language Processing
The are again two things here –
- Working with Data
- Visualizing data/ Generating ingishts
Someone who works with Data can be a Data Analyst or a Data Programmer.
Someone who uses tools like Tableau/ Power BI to prepare reports is a BI programmer, Business Analyst or a Visualization Except.
Generating insights part can be something that both Data Programmer or the Business Analyst can do.
All of these roles have their own set of skills and tools for specialization.
Someone who can do all of these roles, is a Data Scientist.
The final important thing to know is – Analytics is a not a new thing. While few of the above things are relatively new but they are just tools to Analyse data. Before analytics developed and even now, a lot of firms use Excel to depict and understand data. Simply put, if I have the sales for a stores for 5 years, I can see that the sales tend to rise around the second half of the year due to all festivals and things. I just need to use my simple logic for this and no tools are required. These patterns are different in all the different countries. While in India, the spike in sales starts around August and dies around November, In America, we see the trend start around October mid and dies a little while after New Year. This is called seasonality.
Another simple example could be that you have around 1000 visitors to your website every month. Suddenly in one month, the number of visitors in the excel was 10000.. you know there hasnt been any changes or promotions. So the likely explanation is that the data is incorrectly entered.
Apologies for making the gyaan so huge but it was important for the two points required to answer your question and I wasnt sure how much of this you knew.
To get an opportunity into Data Science, you must know two points –
a) What kind of role you aspire for
b) How much are you willing to learn?
While the first point is definitely around something out of the above that calls your interest and you would like to do, the second point is much about the fact that Data Science is evolving. Like I mentioned seasonality. Sometime ago, when the term did not exist, there would have been analysts who would have done some coding or done excel sheets to find these trends which were similar over the years. But now its a concept. It is something you need to know and always take care of or account for. There are always new studies going on and new technologies or softwares coming up, that you need to learn. The question here is – are you ready for such a life?
About the first point, kindly take into consideration about your personal goals – such as, do you enjoy going to clients or staying behind the scenes? Do you find yourself better with data or better with analysing data? They will help you make the choice.
To get a job, I know it is hard at these times but dont worry. It might be some struggle but you will find a job. The important thing is that no matter what job you get, take all the time in the first two years to study and master everything you can. It is very important to understand a wide variety of concepts and tools. Then you can always choose something that interests you and grow horizontally in the same.
Additionally, today if you think of being a BI Expert but tomorrow, you wish to be a Data Analyst – this can be easily done but again with some work and efforts on your part.
The good thing about Data Science is that the demand is growing and so you will be able to find a lot of jobs.