When I was working as an Analytics Manager/Data-scientist, I have often been asked what I am doing or which techniques I am using in my day to day job, dictionary.com describes analytics as

the analysis of data, typically large sets of business data, by the use of mathematics, statistics, and computer/ software.

While this definition is correct it does not truly shed light on what analytics really entails and what skills are necessary to be successful in that domain. I’ll try to shed light on my personal opinion on the matter.

Analytics is all about surfacing business’ data, this can be in the form of dashboard, presentation, reports, ad-hoc analysis or in the form of business modeling or customer targeting.

It is a broad term, with different skill set required according to which function and business area you work on. I would break the skills necessary for analytics in 6 different categories: Databases, Domain knowledge, Excel & Visualization, Statistics, Scripting and Linux.

While domain knowledge will always be needed, depending on which area of analytics some of these skills would be optional or needed to a different extant:

Business & Web Analyst: For business and web analyst, the only true barrier tends to be good Excel knowledge. As such it is a good way to enter the analytics field. Web analyst might need to be proficient in other softwares such a Google analytics or Omniture, but these tend to be relatively easy to learn. Some positions might however require knowledge of different skills categories, knowledge of databases being relatively frequent.

Operation Research & Insight Analyst: Statistical skills and databases knowledge are the bread and butter of this job family. Be it 6 sigma, propensity modeling or some other type of forecasting form the core of these jobs, while SQL tends to be relegated in the background as a way to pull features for the statistical models.

Business Intelligence Analyst & Data Engineer : In this job family, there is a need for stronger database knowledge. Business Intelligence analyst would tend to be more proficient in visualization, while data engineers more proficient in scripting & unix.

Beside the main 3 job families, there are of course other positions open in analytics such as that of Data-scientist which tends to be a hybrids of these 3 families of these families.

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