7 tips to overcome your analytics learning hurdles today

Kunal Jain 20 Sep, 2015 • 5 min read

I have been writing and answering queries on career transition into analytics for more than 18 months now. While this experience has been very fulfilling, I still feel that there is a gap between what I tell people and what they implement. Let me tell this through a few examples:

Mr. A wanted to move into analytics badly. He had left his job and wanted to focus on learning analytics. He had been reading on the subject for some time now and was convinced that this was his calling. When he reached out to me, he asked what, where and how should he start learning about Analytics.

I suggested him to start by taking up a course on edX / Coursera and make sure that he completes all the assignments. When I checked back 3 months after our discussion – he had registered for at least 5 courses Online – completed none, got intimidated by the vast knowledge he needed to gain to make a career in analytics. He was probably more confused than what he was, when he started his journey.


K was an experienced analyst with a big retailer. She had 6 years of experience, but all of it on SAS. She wanted to learn a second (and open source) tool. I thought this would be easy for her. She had a lot of experience in the field and just needed guidance on learning a new tool. I laid out a learning path for her and thought she would take it from there. When I checked a month after our discussion, she had not written a single line of code in R or Python!7 tips to overcome analytics learning hurdles


In these scenarios (and many more like these), people knew what they should be doing and probably had the intention to do it at some point. That is why they would have reached out to me. But they faltered somewhere during the journey. They couldn’t convert their chances even after being in a position to do so.

The problem here was not that people didn’t know what to do. They very well knew what was to be done. The problem was that of implementation and execution. And this is an equally bigger problem. Since, I have not addressed this issue directly in my posts till now – I thought, I would do it now. This problem is some what similar to that of training yourself at the gym – you know the benefits of training yourself. You also know what needs to be done – but still only a few of us are able to train ourselves at the gym regularly.

The key to solving this problem lies in taking small and focused steps with clear mind. The solution lies in taking the first step rather than questioning whether 15th step would be right or not!

Here are a few tips, for people who face challenges in executing their analytics learning plan.


  1. Start out easy (but do start) – This is probably the biggest problem people face – they just don’t start. They know what to learn and where to learn – but they still don’t start learning. They keep searching for more content, more resources – but don’t start with what they already have. Don’t look out for that perfect book or course – just start with what best you have access to. Log on to any MOOC and start learning the subject. Nothing beats action bias! While you start, start easy. Look out for simple solutions. If you have to install a software – look for an executable rather than compiling the code yourself. If there is a GUI version of a tool available – learn on that first. e.g. When I started learning SAS (my first analytics tool apart from Excel), I decided that I’ll use SAS Enterprise Guide – it has a GUI interface and I don’t need to learn the language from start. Once I grew more comfortable with the language and interface, I started picking up the code on the side. This made the process far easy for me.
  2. Define learning objectives clearly – You might face this challenge as soon as you start learning. You start with a video on Business Analytics, find out a term “Business Intelligence”. Next, you search for Business Intelligence and before you know, you are actually watching a tutorial on Tableau! This is the problem of plenty. You need to clearly define what you want to learn and focus only on that. One practice, which has helped me well to do so, is to define these objectives clearly at the outset. Not only do I define what I want to learn, but I also go to the extent of what I won’t learn. For example, when I started learning Python – I had committed that I want to learn Python only for data analysis and not for other purposes (e.g. Web development).
  3. Learn every day – You will likely run in this problem 3 – 7 days down the line. You started well, defined what you wanted to do – but then you ran into something – a new assignment at work, a new commitment to yourself or a new topic within analytics. As a result, you break your learning momentum. The efforts you made would go down the drain, if you do this every time. Once you have decided what needs to be done, you have to make sure that you do it daily. Take out time – however small to learn daily. It could be watching a video for 15 minutes or running a small code – but spend some time daily. You would see how quickly the momentum builds up
  4. Set aside some time – The best way to make sure that you learn daily is to set some time aside. It could be early morning, lunch time at your office or once you are back from work. But set a time aside for your learning and follow the routine. Soon, your mind will become accustomed to learning at this time.
  5. Take one problem, one tool and one technique to learn at a time – Don’t over commit yourself. Quite a few starters I meet promise to learn R and Python in next 6 months. My only advice to them is to pick only one tool. Most of the things which R can do, Python can do them as well and vice versa. By learning both of them simultaneously, you will become good in none! Similarly, learn one technique at a time and work on one problem at a time.
  6. Focus on your strengths – If you know that you enjoy reading – find the right book. If you don’t enjoy coding – start with a GUI tool. If you learn best late at night – learn at that time. Idea is to make learning as simple as possible. Take all the hassle away and just focus on learning.
  7. Do not rationalize – If you were not able to deliver on your learning plan – watch out! Your mind can quickly come up with rationalizations – why you couldn’t learn as much as you thought? Don’t give in to these rationalization. Accept that you failed and start again – but don’t start the blame game. Don’t blame your manager for the extra work or your family for extra commitment – find out a way and start learning.

What do you think about these tips? Have you faced similar problems, while executing your learning path? How do you overcome them? Are there any other tips you can share with us, which can help our audience learn faster.

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Kunal Jain 20 Sep 2015

Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.

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Responses From Readers


sheetal 03 Nov, 2014

Hi Kunal, making a career shift from auditing to analytics, I find these kind of articles by you to be very insightful and encouraging. Currently, I am pursuing SAS certifications- base sas , business intelligence and predictive modeling. When I had started I was very enthusiastic about learning all these. During the course, understanding concepts(technical/statistical etc), coding n all was becoming too much. At some point I even questioned my self that is this the right field for me? My zest for knowledge and make a mark in this field has kept me going n now I know there is no looking back. I will definitely pursue n complete what I have started and continue learning at every opportunity I get.

Vinay 03 Nov, 2014

Hi Kunal, Well written.. Thanks for it :) Hi Sheetal, I am also preparing for Base SAS certification. If you want we can share some material. You can contact me at [email protected] Thanks, Vinay

deepak 03 Nov, 2014

Excellent Article , I am your biggest fan !!!!!!!!!! , "Give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime" and you are doing the second thing which is the most noble thing on this earth .Please continue with your good work

Vinutha 03 Nov, 2014

Hi Kunal, I have a total work experience of 8.5 yrs. I learnt SAS and completed certification 2yrs bacj. Since I did not have work experience in SAS, I was not able to get a job in this field. I am currently working as an Assistant Manager in MIS reporting with 5 yrs experience and also involved in automating reports with Vb macros. I am looking to upgrade my skills in analytics through an online course. I am not specific in terms of the tools i want to learn. Kindly advise on what course I can enrol to which would also helpme make a job change. Thanks....

Harneet 03 Nov, 2014

Hi Kunal, Thanks for the article, these things we all know but never focus on. I myself have committed some of these mistakes. Regards, Harneet.

Karthikeyan 03 Nov, 2014

Super article !!! Practical solutions to learn not only analytics, but anything that we wanted to do newly. Thank you Kunal.

Shashi 04 Nov, 2014

I remember my Professor's quote, in an Information Era the challenge is not learning but how to learn!. You type a key word you get thousands of references/study materials on the web and we end up reading the same few initial lines in all the links. Loosing focus and jumping topics are the other symptoms of this .No doubt, information surrounding us is getting saturated(experts call it as information Tsunami) and it's a timely wake up call from you Kunal. You have neatly explained How to learn? In addition to the above 7 points i have 3 more points which can also help budding Analysts. 8.Techno-Functions: Going forward Analysts role will be more of Techno-Functional in nature. A Techie should show interest in Business and Business guy should learn Technology to some extent. 9. Develop friendship with Numbers and understand the importance of it. You must always carry your company's numbers on your finger tip(say overall revenue, your unit's revenue, Profit, Margin, and your Biz KPIs ). You can add value to your work when you know your competitors numbers on a high level. Read Annual Report to understand the company, go through dashboards/KPIs to understand the business unit. 10. Presentation: You might discover some hidden gems from your data, but it's of no use if you don't know how to present it to the Decision makers. Analysts are not the decision makers instead they influence the decisions. That said, Presentation is neither science nor Maths but it is purely an art work. There are few rules about color combination, real estate positioning of charts/dash board objects etc. you need to practice it couple of times. That's it!

Jatin 07 Nov, 2014

Nice article Kunal!

Pavan 12 Nov, 2014

Hi Kunal, I started my career on Tableau(BI). Right now i'm working on this, I am very enthusiastic about learning all these. I am looking to upgrade my skills in analytics. I'm willing to learn new tools.Kindly advise me.

Sagar 24 Nov, 2014

Hi Kunal, thanks for the article. I am completed B.E in computer engg. in 2013 & now want to enter in analytic field. I have completed Base sas global certification and pursuing Adv.Sas but now days I realize that it's difficult to getting job. I have already registered many job portals but not getting any call back. can you suggest me what was the other way to enter in such field.Kindly advise me.

Arvind 05 Jan, 2015

Guilty of #5. Have been all the algo but practicing none for last 3 months. I realized the mistake and hoping to not repeat it.

Venkat 17 Feb, 2015

Thanks Kunal ! Well written article.

saurabh gupta
saurabh gupta 16 Apr, 2015

hello sir, i am very new to this field... completed btech in computer science in 2012 i would be very thankful if you tell me what to do to get job as data analyst..... what to learn .... in terms of automated tools ,programming languages,

Abhay Goel
Abhay Goel 08 May, 2015

Hi Kunal, I really appreciate efforts you make for betterment of the field as well as guidance to people. It clearly goes to prove your zeal and clarity of thoughts regarding the domain. I solicit some of your advice. Please help.I am a student pursuing undergraduate studies in economics. I also pocess CT-1, CT-3 ( Actuarial Science) to my credit. However Analytics field has started enticing me since I've started reading and researching about it. Following are the points of confusion troubling me for a long time :- a) What is the correlation between Actaurial and Analytics field? b) What should be my next step regarding my career , as in - Should I continue studying Actuarial and switch to Analytics after a brief experience in former domain? OR Shoul I earn some certification in Data Science such as SAS, R, HADOOP ..etc? c) I know this question is vague on my as well as your part to answer. But, on a lighter note , how monetary lucrative is the Analytics field? It would be greatly appreciable if you could answer this with some of the figures as I need to evaluate my oppurtunity cost in terms of other careers. Please help . Thank you in anticipation. Abhay Goel, 9650706180 [email protected]

Aditya 17 May, 2015

Great article Kunal! Your writings always inspires me. Thanks for pointers, I will inculcate some of the tips you suggested above in my learning of Analytics. Thanks once again. Aditya

Anoop Nair
Anoop Nair 19 May, 2015

Ya i want to get into big data and Analytics,i do my studies,but as mentioned in the articles sometimes miss on my goals for a day due to reason.I want to be a good Data Scientist.now that i read your article i shall strive hard no matter what !!,Thanks a lot for helping me correlate my scenario

Manish 19 May, 2015

Very realistic and well written ...Thanks! Just now, you became a helping mind for many...!!

rakesh 20 Sep, 2015

Hi Kunal, Thanks for the Article. And the things which you pointed was not only applicable for analytic's but this was meant for all technologies. Good One. I hope at-least i will realize now and follow what you said. Regards, Rakesh

vinayak karsale
vinayak karsale 22 Sep, 2015

Hi Kunal, I have completed MBA in marketing and have 3.5 years of experience in pharma company as a medical representative now I want to make my career in business analystic so please guide how to move forward.. Need your guidance

Krishna Mohan
Krishna Mohan 04 Nov, 2015

I can relate to different mistakes that Kunal has mentioned in the article - since I have committed most if not all of them. But with constantly catching myself doing the mistakes and correcting them, I can sense that I am getting more and more comfortable with the concepts and numbers. One method that has really worked for me is find others who are interested or curious about Data Analytics and teach them what I learned from MOOC or other readings. This is the best validation of my learning - the False Positives and False Negatives of my learning.

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