Updated: Nov 30, 2019
Looking for "skills required for Analytics” ?.
Before we begin, let me explain to you what Analytics is all about in few points so that the subsequent skill-sets that would be mentioned will make much more sense.
What is Analytics all about..? Analytics is both an art and a science to generate insights from available data to solve any given problem statement.
Its an Art because :
A given problem statement can be solved in multiple ways and some methods would be more appealing than others.
You would need to tell stories through your data (even if it is for business purposes)- a story that your client/managers understand and appreciate. And as we all know “storytelling is an art”.
You will need to present your results using visualization tools, and making something visually interesting is an Art.
It’s a Science because:
Knowledge on “how to use Analytical tools” would be required.
If it is “Machine Learning”, you will need to learn how the various algorithm works and which algorithm should be considered over others on case to case basis.
You will need to understand the business to help the client solve the business problem in a better way.
Now coming to the most-awaited question– What are the essential skills required for Analytics …?
SQL (Structured Query Language) –[Must Have] This is one of the most important (and easy to learn) skills that one must have to begin as an analyst. Knowledge of SQL will help you in querying the databases, handling a large amount of data at ease and relating (joining) Data (information) residing at discrete locations (tables) to make better sense of data.
Excel –[Must Have] This is another ‘must-have’ skill. Excel is very simple and one of the most powerful tools out there. You can do multiple kinds of stuff like Data-Visualization, Data-Aggregation, Pivots, Data-Cleaning/Formatting, Implementing-Formula and much more.
Tableau – [Good to have] This is 'good to have' skill. You can create awesome visualisation and infographic using tableau that would not be possible using excel. You can create interactive dashboards, publish things on servers and have data at real-time.
Python – [Better to have] Python is 'good to have' skill, but if you are able to learn this ‘beast’, it will open a whole lot of opportunity for you. With many of the available ‘libraries’ and a good community online python has not just remained a programming language for developers but have also become a statistical and analytical tool. You can do the following using Python (to name a few): a. Data ingestion b. Data Cleaning c. Data Analysis d. Data Visualization e. Machine Learning f. Automation I will be talking about these in more details in another blog soon..!
R – [Good to have] This is similar to python (Given you just consider the analytical aspect of it). You can choose either of the two. BUT if you ask my opinion I will choose Python as that is much more than just an analytical tool and is a very powerful language if you intend to bring things in the pipeline.
Machine Learning – [Good to have] This is not a tool in itself but rather an approach to solving a problem statement. Predictive analytics is a highly demanded skill nowadays. Machine learning can be achieved using both R and Python. So please stay tuned when l talk about these in detail sometime soon.
SAS – [Good to have] This is another statistical tool used in analytical space. It is ‘not FREE/open-source’. It used to be an important tool in past (and still it is) BUT it is facing good competition from Python nowadays. A trend is visible where companies tend to shift to Python from SAS.
Web-Analytics – [OK to have] This would be an icing on the cake if you possess it. This will not be a ‘must-have’ skill to begin with, but once you have gained some hands-on above skills you should surely look forward to learning things like ‘Google Analytics’ or ‘Adobe Omniture’.
Do let me know about suggestions. This will help me to create better contents for my blogs.