What ‘skills’ do you need for a career shift to Analytics?

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Last month, we explored how you could make a career shift to Analytics.

You may ask what about skills needed to make this transition.

Several questions must be plaguing you.

Do I need ‘deep’ statistical knowledge?

Which tools should I learn on a need-to-know basis?

What other technical skills can get me a good offer?

What soft skills do I need to build up for analytics job roles?

Businesses today are increasingly become diverse and complex. Job roles call for cross-functional skills. For instance, it is no longer enough for a student of Business Economics to be proficient in the application of economic theory to business decisions. He is also expected to understand implications of financial trends and political actions on businesses.

Analytics applies to a range of scenarios and industries, and calls for a great deal of dexterity and span in skill sets. It involves working with numbers, complex algorithms, and a deep knowledge of the problem to arrive at solutions. Organisations typically look for professionals with multi-disciplinary skill sets. Although not an absolute must, the professional who has a range of skills across several functions or domains, is the one who can command his salary package. So now you know why 2015 has ushered in a new trend – that of increasingly domain based streams!



Good tools are building blocks for future needs. Each tool has a different role. Nevertheless, the general purpose tools you HAVE to master are

Excel, R, VBA, and be familiar with at least one front-line tool like SAS, SAP

ETL tools, OLAP, SQL, Data modeling, temporal tables, Visualisation / Reporting tools

Statistics, machine learning


Problem resolution skills, excellent communication skills, on-the-fly reporting abilities, domain knowledge, analytical and logical reasoning skills, willingness to learn new technologies and techniques,  a single-minded approach to testing, flexibility and situational awareness, and sound knowledge of the industry or area of application you are working in.



Python or Java/ Perl, Stata, Statistica, SPSS, Tableau,

Familiarity with cloud tools (Amazon S3), netSuite, Spotfire, Hadoop is  beneficial.

Big Data analytics, analyzing unstructured data, data mining skills


The ability to extend experience and skills to business intelligence, coupled with a diverse domain / application knowledge is the key to success.

Cross-functional skills, deep domain knowledge, ability to think on your feet in a complex, dynamic environment, business acumen, strong persuasion skills, great networking abilities, an established professional networking base, integrity, reliability in complex situations, are usually what get you great references and recommendations.

Bottomline: Short of sounding clichéd, the salary package and career graph in the Analytics landscape has never seemed better! So go ahead, kick-start the process. Arm yourself with technical skills, use DIY freely available material on the net or enroll for a short certification . Drive your career towards an all-new trajectory, analytically.

Recommended Reading (IVY blog)

Why should MBAs consider Analytics as a Career?

Why should Engineers consider Analytics as a Career?

How to land that perfect SAS job?

All you wanted to know about Management Consulting firms and getting hired by one!

Linked in Report – Analytics related skills among “25 hottest skills in demand”

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