Big Data has dramatically altered the information technology landscape globally. So if you evolve faster than technology and learn to tell your story efficiently and meaningfully with data you have struck it big , says Prachi Rege.
Are you a person who likes to make sense out of large amount of data? Are you good with complicated software tools like Hadoop, Java, C#, Python, HBase, Cassandra? Then you must consider a career in the big data industry, which is booming at this point.
According to CRISIL Global Research and Analytics (GR&A), the Indian big data industry is expected to grow from US$200 million in 2012 to US$1 billion in 2015 at a Compound annual growth rate (CAGR) of 83 per cent. ?Naturally, there is a huge demand for data analytic specialists also called as data scientists.
"Companies are now looking for ways of allocating numerical values to various business functions; they require to detect efficiencies, problem areas, and possible improvements. This can be done through data analysis thus providing lucrative job openings," says Arvind Nagpal, founder and CEO, TEG Analytics, a Banglore-based analytics company that helps customers to make better marketing decisions through business analytics. Sectors like IT, retail, banking, telecom, hospitality, which are in the Business to Consumer space are hiring data analysts in large numbers.
The employment scene is promising even globally. Gartner Inc. an American IT research and advisory firm, forecasts that global market demand will reach 4.4 million jobs by 2015. However, only one-third of those jobs will be filled. "It is difficult to find data scientists who have a good knowledge of math, statistics and different technologies. Moreover, as the big data space is fairly new, we have to rely on newbies rather than hiring experts," reflects Srikant Sastri, co-founder, Crayon Data, a Singapore-based analytics company.
Data scientists collect, organise, and interpret statistical information. So what is a typical work profile of a data analyst like? Their work revolves around business challenges of their client. They first gather relevant data from the enormous datasets through hosted IT platforms. Next, the collected data is run through analytics system using software such as SAS, SPSS, XLSTAT, etc. The output from the software determines the solution for the business problem, which is then discussed with the client. "A data analyst provides his/ her clients with insights in business, and helps in building feasible business models for better decision making," explains Sastri.
Candidates with Bachelors or Masters degree in Math, statistics, economics and computer science or related fields may get into this profession. Those with advanced computer science degrees or PhDs in subjects such as physics, biology or social sciences are also hired.
"A data analyst should not only have a strong business acumen, but also the analytical ability to turn data findings to conclusions and conclusions to insights," says Nagpal. Good communication skills are important. As the skill-set required for this industry is highly niche, the remunerations are also very competitive. "The starting salary could be up to Rs 12 lakh," says Sastri.
"Analytics companies recruit people who love numbers and can simplify complex ideas. People with a filtering mind that can scan, store and prioritise all the information captured around their five senses fit the bill," points out Nagpal. So if you enjoy working with data in different ways, experiment with visualisation techniques and have an eye for details and if you have good IT skills, then you could find your niche as a data analyst.
A Business Analyst analyses specific business problems and derive answers from the same using an array of analytical tools. S/he should be proficient in statistics in order to interpret the statistical results and link them to the business context. A business analyst who works in the financial risk space is called a risk analyst. S/he should have in-depth knowledge of portfolio trends, collections forecasts and credit risk adjudication models, etc.
A Subject Matter Expert or SME has specialised knowledge about a business function. S/he works closely with a business analyst to help them understand the data findings in the right business context.
A Statistician has the knowledge of statistical and modeling principles and tunes out chance findings from really significant findings that will repeat over a period of time. S/he sets the path for the whole team by creating an analytics plan that can peel different layers of data in a step-by-step fashion.
A Delivery Manager is responsible for the team, which collects, analyses and interprets the data. S/he also interacts with clients, keeps the projects stays on track and inspires the team to look beyond the obvious to uncover the hidden insights.