Can You Think?

Can You Make a Decision?

If your answer is "Yes" for both these questions ... Well, you are already an expert in Analytics.

What is Analytics?

Analytics is the discovery, interpretation, and communication of meaningful patterns in data.

Well, this definition can be a bit confusing to many people. So, what in actuality is Analytics?

Let us take an example to understand it properly. Imagine you are stuck at your home because of Covid19 lockdown and every shop you know is also closed. There are police personnel with their batons waiting for someone to come out.

Now you got to know that your ration supply is getting low day by day. So what will be your plan of action?

You will go out and buy some more supply and for this, you will consider several factors, such as;

• How many people do you have to feed?
• What is the closest shop that will be open?
• Should you go on a bike to get 'aata' (flour) and bring 'suji', as the police would start a lathi charge?
• What are the things necessary to eat when you are at home?
• Do you also need medicines with a normal food supply?

If you have answers to all these questions, you are an expert in analytics, and here is how;

Well, Analytics is nothing but thinking about all the scenarios that have happened (description), are happening (description), might happen (prediction), and best ways to choose (prescription).

If you will take the above example, the first question is more of asking for a description i.e., the number of people in your family or your flat during lockdown.

Therefore this is part of 'Descriptive Analytics'.

Now you can directly say there are 4 people in my family and can make a beautiful chart and represent all the details of the people living with you, like age, demography, and the place they belong to, and can also add all the geeky stuff in a graph or some pie chart.

The second question is also representing the same. It is asking for a description of the distance of 'n' number of shops in your locality. So, it is also part of Descriptive Analytics.

Now, look after the third scenario, it is asking, should you go by bike and risk yourself with a lathi charge by police or should you go on a walk? Well, in this scenario, you can take the example of several other people who have gone by walk or via bike and create a time series analysis to estimate if people who have gone via bike have got more lathi charges by police or people who are gone by walk. So, when we are trying to predict whether or not we are going to get lathi charged based on historical data, it is known as Predictive Analytics.

Now, there is one more, if you are prescribing your friend who looks at people who have gone out to longer distances on their bikes and have had some instances with police, then this is more of Prescriptive Analytics.

Have you seen one thing? You were using Analytics from the day you were born.

Shall I cry, then only I will get food to eat?

Shall I put tantrums, then only I will get my favorite game or comic book?

The reason why people are afraid of Analytics is because some people have made sure that we will drag Analytics to programming language.

All the World’s Analytics is Common Sense

Have you ever heard, that you should be an expert in statistics to understand Analytics? Well, that is true, but this makes people more fearsome. This is because we have only seen statistics as a chapter in maths books. Remember, statistics is a part of applied mathematics. For Example, there are 4 Apples, 3 oranges, and 6 Potatoes in a basket, so what is the frequency of fruits in the basket?

The answer is 7. And it was not rocket science, right?

Why do we use tools like RStudio, Python, and Tableau in Analytics? It confuses me a lot and I don't have a programming background, how do I cope up with it?

This is one of the most interesting questions whenever someone thinks of taking Analytics as his or her subject further. To answer this simply, one needs to get fear out of their mind. This is because, if you know Analytics is just common sense, and to analyze every scenario, you will understand, we can’t do it with our bare mind.

If you are good at finding solutions, you can solve huge Analytical issues in a simple Excel Sheet.

The reason why we use some analytical tools like RStudio and Python is that we can calculate every scenario on a sheet of paper, but, It is not practical. Imagine calculating one Analytical issue and then not being able to reuse the model to apply it to another problem.

Using these tools enables us to reuse already-built models to solve complex issues. Imagine schools making you again create the theory of relativity. E=mc².

But that is just a waste of time and money.

And for people who say they are afraid to code, remember one thing, you were never able to speak Hindi or English or your mother tongue when you were born. And to make it more obvious, we don’t have to code in Analytics, we just need to see, which formula to use where. But slowly and steadily you start understanding the codes and then you start modifying these codes and generate different results altogether.

Now, if fear of analytics is out of your mind, I would like to describe why it has become more difficult for people to differentiate between Analytics and coding.

For many years, Btech students with good programming knowledge have started exploring streams where programming could be used. Now, students from computer backgrounds have started entering into Finance, Marketing, and now in HR as well.

As they already know how to program, therefore they can make awesome apps and systems for their departments, which keeps them in the highlight and others automatically go in the limelight. This is dangerous as many skills are also becoming extinct because of this issue and because of this team managers now want someone who can code and make some easy system to a day-to-day issue.

But this should not make you demotivated. This is the time when you can stand up and say, ‘A good programmer can give you a system as per your requirement, but a person who has core knowledge of the subject can provide solutions that a programmer can’t’, and we can hire anyone to create an app or system if the problem is recurring in nature.

This is time to upskill ourselves with programming knowledge, but one should not see it as a drawback as people who have spent their whole lives in a particular department, have a gold mine of knowledge and he is more valuable to the organization rather than introducing someone who can code and create systems.

Remember, you need an architect first to create a plan and provide data to create the system. Any engineer or construction worker cannot solve an issue that he has seen first time in his or her life. Some experiences matter most and this is something that weighs more than technical knowledge.

By saying this I am not trying to demean any subject or background. But this is the reality. Most of the students become confused because we are not able to assist them with proper guidance regarding a particular subject. We should teach students to see the practical use of Analytical Tools and not just raw coding.

We should not show how to create Word Clouds first but try to explain why Word Clouds and Sentiment Clouds are important and how we can create them in the easiest way possible.

Has anyone told you, that you can make a Word Cloud using MS Word?

This is just an example of why we make a particular thing so complex. We make students make Word Clouds without making them understand they can make it easily with just two clicks on MS Word.

Also, we never try to make them understand what is used in every line of the code if we are using tools like RStudio or Python.