Analytics Education

Gaurav Vohra | April 27,2011 10:05 am IST

In this era of information, analytics has become an integral part of running a business. More and more companies are swearing by the power of data mining and analysis and data-driven insights are complementing experience and intuition when it comes to decision making.


Knowledge of analytics – what it is, how it works, what it can do, what it cannot do- has become a key criterion for becoming successful at work place. No wonder that academic institutions of all kinds are striving to provide this knowledge to their students.


Analytics in India
Analytics has taken off in a big way in India as India becomes the global centre for talent in the field. During the early stages of analytics evolution (2000-2010), most companies like Genpact, Symphony, Inductis etc. were looking to hire bachelors and masters in Statistics and Economics from institutes such as Indian Statistical Institute, JNU and Calcutta University. As demand for qualified resources grew, the pool grew to include graduates, postgraduates and PhDs from all quantitative streams such as Math, Science, Commerce and Engineering. Now, BBAs and MBAs are also making their mark in the field.


Lack of Trained Resources
While India has a large pool of Statisticians, Economists and MBAs for companies to hire from, none of them come equipped with all the skills that today’s employers are looking for. Companies spend precious time, money and resources in training the new hires on the skills required at the work place.


Analytics Training in India
Analytics training options in India are severely limited at this point of time. Some of the largest B-schools like IIM Calcutta, IIM Bangalore and SJMSOM, the MBA college of IIT Bombay have all started certificate or diploma courses in analytics and advanced analytics. Most of the courses are of 1 year duration and are either part-time or full time. While these courses have a comprehensive curriculum, they are again not designed entirely around the needs of today’s workplace. There is too much emphasis on theory and very little exposure to practical and real-life business problems. About 75% of what is taught is not really required in business but is more suited for research.

 

Exposure to analytic tools and software is limited to screen shots and this is a big handicap for anyone looking for a job in analytics.


There are several small training institutes that are trying to fill the demand-supply gap in analytics. However, most of these institutes do not have a rich enough curriculum. They are either training students to be a SAS (or any other tool) programmer or are focusing on a very narrow segment within analytics.


The high cost of analytic software is another deterrent to analytics education. While universities in the US get heavily discounted academic licenses, Indian training institutes are not eligible for those. A popular tool like SAS or SPSS could cost lakhs of rupees annually and this increases the cost of analytics education.


What makes a good analytics training?
Training in analytics needs to focus on 4 different things.
• Statistics for analytics
• Modeling methodology
• Analytic techniques
• Analytic tool training
• Soft skills for analytics


Statistics: Analytics requires an understanding of basic statistics and certain advanced statistical concepts that are widely used in analytic techniques. Those who have a degree in Statistics or Economics will have enough knowledge of this subject. Others will need to be trained on statistics as it is used in analytics.


Modeling methodology: Knowledge of modelling methodology is crucial for any analytics project. There is a sequence of events that precedes and follows the actual predictive modelling. Starting with an exploration of data to preparing the data for modelling to validating the model results – there is a time and place for every step and it is important to understand this sequence.


Analytic techniques: Analytic techniques include popular ones like regression, ANOVA, decision trees, clustering etc. There are also domain specific techniques that come in handy. For example, price promotion analysis for consumer goods, market basket analysis for retail, churn analysis for telecom. Any training on analytics needs to cover the most widely used techniques.


Analytic tool training: There are a large number of different software available in the market for analytics. Some are script based, some are GUI based. While it is not possible to train on every available software, it is a good idea to be trained on some of the most popular tools like Excel and SAS language or the R software. You can read more about the popular analytic tools here.

Soft skills: Soft skills are important for any job. However there are a few skills that are more specific to analytics. For example, being able to explain complex modeling results to non-statistical people. Any analysis is only as good as how the results are presented. Too often, analysts get too involved in the methodology and algorithms to be able to present their results in a manner that is understood by lay-people.


Finally, analytics education has to include exposure to real-life business situations and data. Real business data is very different from the ‘ideal’ research data that students practice on. It is important that the training methodology includes working on case studies and business projects so students are able to translate what they learn in class to what is used in business.


To learn more about analytics, visit the author’s blog.

 

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Gaurav is an IIM alumnus with over 10 years of experience in the field of analytics and has worked across multiple verticals including financial services, retail, FMCG, telecom, pharmaceuticals and leisur...

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Comments


Shameek Roy Chowdhury on 05/04/11 at 11:01 am

I really like you article here. As I am interested in pursuing a career in Financial Analytics, I WOULD REALLY APPRECIATE IF YOU COULD SUGGEST ME A TEXT BOOK ON-Predictive modeling, statistical modeling, forecasting, CHAID, modelling, credit risk analytics, score card, cross sell, loss forecasting,ETC.