How to become a Business Analyst in 3 months?

Hello readers, here is the third post in our Towards Machine Learning series and we would discuss the path to become an analyst here. If you are new to this, you can always start with our episode-1 and episode-2 before coming here.

“Business Analyst” is probably one of the most abused terms in the job market right now. The word looks fancy, the pay seems to be good and everyone around you is one now. But very few really know what they really do and how they do. I was one of those guys who had no clue about being an analyst a few years ago when I wanted to become one, very badly and it took me 3 years to be here.

At the end of this 3-year journey, I realized the three important things that actually made a difference in my life.

  1. Learn: If you want to get good at what you do, learn more, learn often and learn every day

2. Practice: If you want to get better at what you have learned, practice it till you master it and then move on to the next thing

3. Teach: If you want to get great at what you have practiced, teach it. You need to learn and practice more than ever in your life to teach it. The enthusiasm of the people whom you teach would make you a great at what you do and also, a better person!

When I started looking for opportunities to learn “Analytics” I was not sure where to even start. But as luck had it for me I found a mentor to help me wade through this rough waters. With his help, I prepared a yearly plan that set on to the path of the becoming an analyst.

I know how intimidating it can be to make a big career move, so we’re here to help you take that first step. If you are like me from a non-programming background but interested in analytics here is a small plan that might help you.

1. Basics:

Math and Statistics form the core of any analytics or computation that you are going to handle in your life. Having this skill set would go a long way irrespective of what you become among a data scientist, business analyst or an ML engineer.

Based on the interest and need you can dig deeper to learn more & specific topics catered towards your requirements.

Where to learn: There are a lot of free courses available to learn them online. You can pick and choose from the list based on your preferences. I would put down a few options in the cheat sheet below.

2. Computer Science:

There were a lot of times when I cursed myself for not learning any programming language in my college. Basic programming knowledge would be of great help in your initial days when you want to focus on the logic part than the language. All is not lost for those who have no prior experience in coding as the entry skill level here is very low for an analyst.

Although SQL is not a programming language I cannot stress enough to make sure that you check this one off your list before you step on to any other language.

There is an entire world divided on this and I would love to stay out this fight. Python vs R, pick one that you are comfortable with and you would realize that they are not really very tangential as you work more on them. So, don’t worry about this as a blue or red pill test. Choose one and go with it, for now.

Where to learn: Again, there are a lot of free courses available to learn them online. I would put down a few options in the cheat sheet below.

3. Data, data, and data….

Perhaps the word that you might be saying more than your mother’s name in your lifetime, data. You will start with learning to see data everywhere around you from your mobile data usage to Netflix movies you watch, you realize that everything and anything that we do now can generate data.

You need to start learning on what makes up for data, types of data and their properties.

Where to learn: This is a very tricky one as you could get stuck in an infinite loop here forever learning more and more about this. It would help if you can start with finite timeline and goals before getting started. I would put down a few options in the cheat sheet below to get started.

4. Data vs Knowledge

Now that you have realized that data is everywhere around us it’s your job to make some sense out all the noise there. “Data vs Knowledge”, is what I love to call it.

Your job would be is to find patterns, common rules, and logic that stays hidden in the piles of data that is thrown at you. This is the most fun part of the entire process where you can come up with actual insights, recommendations, and solutions too. But it’s a long journey to here where you need to work on all other skills before we reach this promised land.

Where to learn: This requires knowledge on commonly used algorithms, techniques, and more importantly practice. You learn a model, solve a problem on Kaggle and find ways to better it. And repeat this process until you become really good at what you want. I would put down a few options in the cheat sheet below to get started.

A long way to home….

The woods are lovely, dark and deep,
But I have promises to keep,
And miles to go before I sleep,
And miles to go before I sleep.

— Robert Frost, “Stopping by Woods on a Snowy Evening”

I started with the basics and gradually moved up the ladder thanks to the set plan in place. I don’t boast of being great at analytics but I am definitely better off than I was a few years ago and am sure that there is a still a long way to go.

All of this is just a very high-level path that helped me to reach here from a very confused state I am in a few years ago. There is no silver bullet to solve all your problems and assure you that you would become a great analyst. But that’s the whole point of analytics, isn’t it? We deal with uncertainties and probabilities to minimize the errors. This is the world you are entering now!

Here’s the cheat sheet, click on the link below and you can copy the sheet onto your drive or spreadsheet and use it.

Happy hunting!

Ciao for now.