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A journey to analytics career: Road less travelled

Posted by trainedat on September 2, 2016
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Analytics has adopted by companies so much over the past few years that it resulted in lack of right talent.  Every company is in a continual search for an analytics expert. A successful analyst should have both data mining knowledge and business knowledge. The question is which one is the most important aspect in an analytics career. This can be best answered by an analogy that later is the oil and the former is the steering for any analytical project. Both are equally important to a successful analytics career but serves different purpose. You will not be solving the right business problem if you lack business understanding. On the other hand, without using the right data and technique to solve a business problem will not result in quality and actionable insight.

Analytics career

Gone are the days when only a mathematician or statistician or engineer can become a data analyst. Even people working in the core business of a company can make transition to the analytics if they do the right certification and training. It has become common that professional from HR, Sales, Marketing and Call center professional are making shifts to analytics. Picture below provides details on what are the various streams of analytics and suggest what people can make a shift to these streams from businesses.

Analytics career Roadmap

 

Type of Analytics

Most famous of these are BFSI, sales, marketing, supply chain and retail analytics. Customer Intelligence is the common  task in all of these.  Propensity model and market basket models are commonly used to drive insight regarding customers purchasing patterns. Forecasting is also very popular and sought after skill to have in the industry. Supply chain analytics need some of the more advance operations research skills like optimization and simulation modeling.

Web analytics and digital marketing is also quickly gaining the traction. Cookie analytics and A/B testing are some of the popular techniques used in Web analytics. Search engine optimization and campaign analytics is now quintessential in digital marketing.

HR analytics and call center analytics also essential in workforce management and productivity improvement.

 

Hiring in Analytics

Traditionally companies hire fresher to do the reporting and data management work and seasoned professionals to do the more advanced data science projects. A common analytics career path of a data management person into analytics is through reporting and dashboard development. After gaining enough experience and with right courses and certifications they moves to more advance data science projects. Similarly a business domain expert may end up managing reporting team initially and later handle more advance analytics projects.

Recently, due to high acceptability and adoption of Big data technologies a lot of IT professional has made switch into analytics via having Big data knowledge. The level of programming in analytics tool such as SAS, Weka, R and python is not as difficult as required in software development , however a right combination of technical skills with data mining and business knowledge make the successful analytics career.

 

With the advent of online MOOCs like Coursera and EDX and even good classroom training, it has become even easier to learn advance theory of data science and get renowned certifications.

I would end the discussion with a final note that the best investment is the investment in oneself, so keep learning and have fun!

 

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