10 questions about career in analytics

Analytics can simply be defined as the process of breaking a problem into simpler parts and using inferences based on data to drive decisions. Analytics is not a tool or a technology; rather it is a way of thinking and acting.

1- Why is it becoming so popular?

Analytics is becoming fundamental to many businesses around the world. With enormous amounts of data at their disposal, businesses no longer feel the need to rely on intuition when making strategic decisions. Analytics can

  • Help airlines forecast the demand for their seat months in advance,
  • Assist hotels to predict room occupancy,
  • call centres to predict call volumes,
  • even football clubs predict which players are under-priced in the market

Here are some articles on the usage and popularity of analytics

Popularity of analytics

Heritage analytics competition

IBM bets big on analytics

2- How can I build a career in analytics?

Do you love to explore and investigate information? Do you find spreadsheets to be a useful ally rather than the scary monster people make them out to be? If the answer to both the questions is yes, you should consider a career in analytics.

Here is a list of articles on how to build a successful career in analytics.

Key skills for a successful analytics career

Career in analytics in a KPO

Starting off in analytics

3- I already have 5 years of experience in the non-analytics field. Does it make sense for me to make a career shift into analytics at this stage?

Analytics is finding applications in all aspects of businesses in all kinds of industries. The ability to understand and analyse data is becoming more and more sought after in terms of skills today’s employees are looking for.

Even if you are from a non-analytical background, making a switch to analytics can be a rewarding one in the long run. The starting salaries in analytics range from 4 to 7 lacs and the career growth is pretty fast in this field. Further, the experience of dealing with and analysing information to influence strategy will prepare you for management roles down the line in your career.

Additionally, if you are from an industry like financial services, telecom, retail, health care or any of the other analytics-dominated industries, your business experience will provide an advantage in an analytics role too.

4- What are the popular tools used in business analytics?

Business analytics is currently dominated by SAS, a statistical analysis software. IBM’s Modeler (previously SPSS Clementine) is another popular tool. Knowledgestudio is a widely used software that is most popular for its decision tree functionality.

Microsoft Excel is probably the most widely used analytic tool across all industries.

R and Weka are 2 of the popular open source analytic tools.

SQL knowledge is also beneficial to have.

Here is an article on some of the popular analytic tools.

5- What are the different skill-set components that are sought after by employers in analytics?

There are multiple skill set components that are required to be successful in analytics.

  • Knowledge of Statistics – While it is not necessary to be a Statistician in order to become a business analyst, it is important to have an understanding of basic statistical concepts that have wide applicability in business analytics. Concepts like measures of central tendency, measures of dispersion, hypothesis testing, probability, distributions etc. are essential to analytics and one must have a good understanding of these topics and should be comfortable applying these concepts to business situations.
  • Knowledge of the modelling methodology – 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, and 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, and 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 modelling 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.

6. How does Jigsaw Academy’s Foundation course help kick-start a career in analytics?

Jigsaw Academy’s Foundation course is designed for those looking to build a career in the field of analytics and who have limited or no prior exposure to the elements of analytics.

The Foundation course covers all of the skill set components mentioned above and is designed keeping in mind the skill set requirements in today’s workplace. You can read about it here

Our faculty consists of experienced analytics professionals from around the globe. We provide strong industry interaction for our students through guest lectures taken by analytics veterans. To view our faculty profiles click here.

We have a strong network in the field of analytics. We are constantly in touch with various companies for their hiring and training needs. We identify the right opportunities for our students and help them get in touch with the relevant HR teams.

Our soft skills module focuses on how to prepare for a career in analytics through courses like “Resume building for analytics” and “How to prepare for an analytics interview”

7. How can I participate in Jigsaw Academy’s Foundation course?

Jigsaw Academy offers its courses on a virtual platform. This means that you can attend the course from anywhere around the globe as long as you have access to an internet connection.

Virtual classrooms offer incomparable convenience and flexibility. You can access a virtual classroom from home, office, internet café or any other place which has an internet connection.
You don’t even need to waste time travelling to the training centre. We bring it you right at your desk.
Virtual classrooms help us bring experienced faculty from all over the world to you.
You don’t need to fall behind or spend extra time catching up if you miss a class. All sessions in our virtual classrooms are recorded. You can watch and listen to the entire session at any time.

Our Virtual classrooms offer audio, video and text interaction. Students can ask questions verbally or by using the built-in chat functionality. In fact our students prefer text interaction when the lectures are going on. Instead of interrupting the presenter each time, students use the chat window to type in their comments or questions. The teacher then addresses all the comments/questions when he/she takes a pause. This works better than a traditional classroom where the students have to either interrupt the teacher’s train of thought or remember to ask the question when the teacher pauses.

8. What do the students have to say about Jigsaw Academy?

“The syllabus is exhaustive covering SAS and various analytical methodologies. The instructors are very knowledgeable and always eager to guide/help. More importantly through this course, I feel comfortable working with and deriving inferences from huge amounts of data. The training through the virtual platform is seamless with no connectivity issues and is as good as a virtual classroom can get. Weekly assignments help to strengthen the concepts. A good investment indeed! Thanks, Jigsaw.”

Meghna Govil,

Masters in Computer Science, University of Texas

“After completing my training in business analytics from IIT-Mumbai, I almost felt a sense of defeat. While I had gone through several hundred pages of Econometrics and Statistics, I was not able to apply my education.

Your programme helped me to snap out the academic mode in style! Within 6 weeks, I found myself burning the mid-night oil trying to code analytics solutions in SAS on live data spanning thousands of records. Something I had not imagined I would be doing so quickly.

Sarita is a thorough professional and her real-world experience shines through in her teaching style. Looking forward to training with you folks on the advanced modules!”

Ashish Merchant,

Vice President – NetCarrots Loyalty Services

“To be frank, any skepticism I had before joining Jigsaw’s course has disappeared after these first few sessions itself. The training content and the quality has been excellent thus far. The case studies and real life business examples accompanying every theoretical concept makes understanding so much easier. It is so obvious that this kind of knowledge transfer can be imparted only by experienced professional’s. If not anything, my confidence in analytics is only rising week after week.”

M.S. Dinesh,

Design Engineer, Honeywell

9. How can I contact Jigsaw Academy?

Email Id – info@jigsawacademy.com

Phone – +91-9019217000

Website – www.jigsawacademy.com

Interested in a career in Data Science?
To learn more about Jigsaw’s Data Science with SAS Course – click here.
To learn more about Jigsaw’s Data Science with R Course – click here.
To learn more about Jigsaw’s Big Data Course – click here.

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