As diverse as the field of analytics, data science and big data is, the pool to fish knowledge and achieve erudition is even vast. And despite having begun the careers with a basic idea of what the industry is all about, most of the professionals are left with an instinct to further hone their skills. Rightfully thought, but whether a newbie or an expert, one might bump into just too many options making it difficult to figure out which one to pick.
So here we come with answers to the most common doubts donning the list “how can the knowledge in Analytics be increased?”, “what kind of training should one be looking for?”, “how and where can one learn them?” Let’s begin the steps of identifying the right training for you:
Define your goals:
It’s important to know what you are looking for. Are you looking to be a data scientist, or a Hadoop developer or something else. These profiles being very different, needs different treatment in terms of training. And that’s why deciding upon your area of interest becomes the first point.
Most of the candidates look out for analytics training with an aim to indulge into the field as quickly as possible and hence majority of courses in India provide a complete overview of analytics touching various aspects of it, which is not a bad idea. But the flip side is that there are very few courses that go deep into certain aspect of analytics/ data science. For eg: there are very few courses available that go deep into the data visualization. As a result of it most of the training and courses becomes just an overview of discipline like analytics and there is little depth that remains.
So it becomes important to decide, what is it with the field that you want to explore. And if your goal is to get an overview of the complete field, then yes, there are a large amount of courses available in all modes- online/ offline, short term/ long term, certification/ degree, distance/ on-campus.
Identify skill gaps:
As pointed out earlier, the skills required for business professionals might be different than those required for big data analyst and hence the next step is to identify those gaps, filling which can take you a notch higher.
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Having a quick glimpse on the basic skills required by data scientist, SQL skills, hands-on experience of the basic “Data to Decisions” framework, applied statistical techniques ranging from basics such as profiling, correlation analysis to advanced ones such as predictive analytics are a must. On the other hand, those with an inclination to business profile must have the skills to work effectively with data scientists/analyst, should be able to access data through various tools such as Business Object, Microstrategy etc., amongst the various other skill sets mentioned above.
For those diving into the industry afresh, getting a flavour of data science and knowing more about the industry is the first step. And you can do so by accessing free resources available online. Get yourself started with YouTube videos, coursera, edx and more. The only thing to be kept in mind is to have a sure shot feeling of being in the industry before jumping into full-fledged trainings.
Do your research:
Once you have figured out what is the kind of knowledge that you are looking forward to seek, discuss with your friends and peers who have had similar goals as yours and learn what training they found necessary or helpful. Browse through online resources to get a fair idea of the options available.
There are many institutes/ B-Schools offering long and short term courses to get you well acquainted with the analytics/ data science industry. Starting from masters to diplomas and certification courses, there are a lot of options offered by these institutes which can be selected based on your requirement.
Choose the right option:
Scrolling through what all can be done, there are various master degree programs in analytics which often offer statistics, computer science and general managerial skills as a part of the curriculum. These programs are handy for those who are looking out for a fresh opportunity in the industry with no prior work experience.
Home » How to choose the right analytics training for you
Now, a decision to go for a short term or a long term course is purely based out on how much time and resources that you are willing to devote to enhance your analytics knowledge. It’s a simple equation, the time spent by you for training is directly proportional to the knowledge that you gain out of it. But again, an individual’s overall motivation and the quality of training you chose very crucial.
Coming to the modes of taking training, whether classroom or distance depends solely on you. Having said that 75% of analytics courses available today are through distance/ online based, which means that you can rule out the location you are based out of, as any sort of deterrent in availing these training.
Just one point to be kept in mind here: in any of the above modes of acquiring knowledge, having a thorough practical experience focused on solving real-time business problems is a definite add on. Especially for those looking for a transition in career, an access to analytics experts and working on a real time project should be a must.
Growing step by step:
Keep adding to your knowledge base. If you know nothing, begin with learning excel. For the starters, it’s always a good idea to have a thorough learning in SAS/ R/ Python, which are considered the Bible of Analytics field. The steps could further be taken towards learning QlikView / Tableau / D3.js and NoSQL Databases and so on.
Though we now have a thorough idea on how to get the right training for analytics, the results of these training depends solely on you. Not falling in the herd but choosing the program that suits your requirements would only yield you the desired transformation in your career. So dive in and explore your hidden treasures!
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Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures. Contact: firstname.lastname@example.org.