Sangeeta Dec 23, 2013 No Comments
Before you plunge headlong into analytics as your chosen career path, you need to know whether you are have the right skills for the fast developing analytics industry.
Once you are confident you have what it takes to be a data analyst or scientist, the next logical step is to explore the analytics career path. Whether you are a fresh student or a professional looking to migrate into the analytics career domain, these are the 5 things you need to know.
#1. What does the Analyst do?
The analyst works with numbers, i.e. information in data structure and translates this into a meaningful form. This involves processes related to data collection, data mining, organization and interpretation of the same for decision making.
Every business collects data, whether it is customer data, sales figures, transportation costs, monthly billing or logistics of a new operation. The analyst uses the data to solve existing problems, increase business value and make better decisions for an effective ROI (Return on Investment). Depending upon the company or client requirements, an analyst works data to help increase sales, make decisions about expansion and location identification, reduce transportation costs, evolve an effective pricing, identify areas of cost cutting to predicting election results. The nature of the job varies for different industries, clients and problem resolution. So the role of the analyst for a retail company would differ from that of one working in a KPO firm currently working on a project related to Government healthcare. Likewise, the analyst role also differs for clients, as one client may require the analyst to arrive at decisions on human resource cost cutting, while another t may require real-time analysis of website data. The analyst in his role of problem solving, drives data for business reporting, efficiencies, make suggestions or predictions.
Different types of analysts function in the realm of the analytic industry, defined by the roles they perform. So you have data analysts, operations analysts, risk analysts, marketing analysts, business analyst, web analyst, and so on. These are primary level analytic roles. Job titles differ across industries, individual companies and nature of services performed by the hiring firm.
#2. What should you learn?
To begin with you need to be a graduate in Mathematics, Statistics or Computer Science; the three core areas of analytic roles. The analyst works in a constant environment of figures, reports, stats and graphs. All of which, run on a Database Management System (DBMS) – a computer program environment that stores, modifies and extracts information from a database. This calls for computing and very often some basic programming knowledge. So if you are graduate in Mathematics or Statistics, you need to additionally learn tools to manipulate data – Microsoft Excel, a Query or manipulation language like SQL and at least one software for analysing data (like SAS , SPSS, R, STATA). Knowledge of DBMS, a programming language like Pyhton, and Reporting softwares can also be added to your learning curve.
Together with a graduate degree, you need to have some diploma or certification in an analytics domain, whether KPO, Risk or Data Science.
For senior level jobs, you need to be a post graduate in your chosen field or any of the above. Alternately, you can pile on your graduate degree with diplomas and certifications in programming, data management, finance, insurance, marketing and the like.
#3. What skills you need to master?
You need to have the ability to see through large amount of data and make interpretations for analysis. So, attention to details and computing skills are the precursor to all other skill-sets.
Above this, you need to have the following skills – analytic ability, communication skills, knack for critical thinking, basic computer knowledge, research ability, report writing and presentation proficiency, visualisation technique and a basic understanding of how businesses work.
In today’s environment, where the analyst role or salary is defined by the level of skill-sets you bring to the organization you apply to, the more talented or skilled you are, the better are your job prospects
#4. How to look for the right job?
If you are a student of an analytics training school, then most likely you will have an access to in-house information of ongoing analyst recruitments in your city and across the country. At the same time, you need to be on the look-out for entry level jobs or firms that are of interest to you. While salary considerations are usually the prime decision factor, you need to first chalk out your individual career path and how you would like to walk it. Would you like to be a part of a small start-up where you can have the opportunity of diverse on-hand training and develop a wide learning curve? Or would you like to be a small cog in a larger company where you can master a given line of analytic role and work with Big Data?
Looking up career sites, registering with analytics placement firms and browsing on the net with the right keywords is the way to go about looking for your preferred analytics job.
#5. When to migrate?
There isn’t a pre-defined maturity curve with analytics proficiency. The day you think you have mastered the right tools, have developed some basic work experience in either a set analytic role like say risk analytics or marketing analytics, or clocked at least a 2 year experience with a KPO firm, you can definitely think of migrating. It is not merely about what you can do, but where you are in the career path. It is about a continuous value creation, so anytime is a great time for making that much desired shift to a ‘fat paying’ analytics job. Keep an updated CV ready and network. You never know who your potential employer is!
The bottom line is that analytics is the biggest opportunity of the century with huge opportunities in the coming years, in terms of both career prospect and salary benefits. All you need to be is focused on your chosen career progression and work steadfastly towards demanding your own salary with acquired skill-sets.