\u201cBig Data Analytics\u201d, \u201cData Science\u201d, \u201cCloud\u201d \u2013 you may have heard of these buzzwords in the technology landscape today. But much like how movies and comedy shows are marketed, these words have been hyped by businesses, industry analysts, journalists, and possibly your neighborhood watchman. Everyone seems to have a perspective on what Big Data analytics is and much like any commodity in the market, there is a\u00a0 promise of an attractive job in the Big Data analytics space.\n\nStudents who are about to start their professional careers or professionals who have spent a few years (2-8 years) in a job related to IT, business, or consulting are now wondering about the potential opportunities that lay ahead of them, how to plan their career progression, and how to begin.\u00a0\n\nIn this article,\u00a0 we shall clear some of the clouds around what analytics is, the roles available in the analytics industry, what skillset will help you get a job in this industry, and how your career can progress if you are already working in analytics.\n\nIt\u2019s common to hear of problems like the following in business:\n\n\n How should we price that new candy we just introduced in our stores?\n Should we carry brand X edible oil in our stores?\n Last week we saw a decline in our sales. What happened?\n If I invest $5 million in marketing and loyalty, how much incremental sales can we expect?\n\n\nThese are only a few examples. Traditionally, answers to these questions relied on the gut and experience of business executives. Another approach though, has been to use some heuristics around data.\u00a0 In simple words, \u201cAnalytics\u201d is to use data to help make these decisions. So, is it entirely a new animal around the block? I don\u2019t think so. However, the science and art of using data have evolved over time and are still evolving. The complexity lies in accessing and preparing the data (this could run into zeta bytes of data, dispersed and unstructured), applying statistical techniques, generating insights\/recommendations, providing a way to enable business users to use the recommendations consistently.\n\nThe primary skill sets required are:\u00a0\n\n\n Business understanding\u00a0\n Appreciation of statistics and the ability to implement some concepts\u00a0\n Ability to use technology for data extraction and processing\u00a0\u00a0\n In addition to these skills, one should possess soft skills such as communication, problem solving, working with teams, present findings, and drive consumption with the business users\u00a0\n\n\nThere are a few roles that are relevant in analytics\n\n1) Analytics manager\/engagement manager -\u00a0This role will be responsible for identifying and understanding the right business problem, as well as to liaison with the business users. They will ensure the success of the overall program.\n\n2) Translator - These folks understand both the business users and the creators and can facilitate a meaningful engagement to drive the consumption of analytics at scale.\n\n3) Analytics Creators -\u00a0These are the folks who will be hands-on in analytics. I see a few flavours of this role based on a combination of business, statistics and technology, though entry level responsibilities will be similar:\n\n\n \n\n Business Analyst \u2013 these folks will possess equal rigor to all the three disciplines.\u00a0\n Data Engineers \u2013 The skill-set of these folks will be over-indexed on technology and less business and statistics\n Data Scientists\u00a0 - These folks will over-index on Statistics\n\n\n\n\n4) Business users \u2013 These are typically business folks who get trained adequately to appreciate technology and Statistics so that they can consume the analytics in their decision making process\n\n5) Analytics Leaders \u2013 These senior folks are responsible for building the analytics organization, ensuring that the right investments are made to develop the ecosystem. These folks will have broader perspectives on the possibilities of using advanced technology and statistics\n\nAll the roles are important in the analytics value chain. So, what does it mean for your career?\n\nIf you are just out of your undergrad or grad school and looking to start your career, you should pick up a role as an analytics creator. In the first 18 months, the flavour you choose wouldn\u2019t matter much. However, based on your interests and learning ability, you may choose other flavours later on. Most likely the organisation you work in will provide you some training to get you going, though that will not replace the necessity for self-learning.\n\nIf you are an MBA or if you are currently playing a business role and you want to explore a career in analytics, you have two choices:\n\n\n Understand some concepts of Statistics and read up on the latest technologies. Continue at your current business role, but equip yourself with better decision making tools\n Learn statistical concepts and technology to become an analytics manager\/consultant or an analytics leader based on your experience level\n If you are playing an analytics role currently, you can acquire more business skills and play a translator\u2019s role that involves driving consumption of analytics.\n\n\nDefining The Learning Path For Analytics Aspirants\u00a0\n\nIf you are an IT professional with 2+ years of experience, you should have good hold on some technologies and an appreciation of business. Based on your experience, you can pick up one of the following learning paths:\n\n\n Learn basic concepts of Statistics and some tools like R\/Python. If you are not already proficient in SQL, you must brush up your skills. Learn at least one visualization tool other than excel, such as Tableau. There are a number of online and offline courses that can help you to learn these skills. Usually professionals with 2-5 years of experience will take up a role in the analytics creator org after this learning\n Learn Statistics from an application perspective and newer technologies at a higher level. If you are an IT professional with 5+ years and with a good business understanding, you can pick up the Analytics manager role\n\n\nIf you are already working in the analytics industry, how should you be thinking about your career progression? If you are not innovating on some technology or algorithm that\u2019s ground-breaking, most likely your career should move towards a leadership role. While you will have incremental learning across business, Math and technology, a leadership role will require stronger soft-skills, such as communication, problem solving, ability to build and motivate teams, interpersonal skills, driving change management etc.\n\nAnalytics is an emerging field. There are newer researches in statistics and technologies constantly which can be used to solve newer problems with greater business impact. So, the key to success is to learn continuously and keeping yourself up to date.\u00a0\n\nIt is important to appreciate that technology and statistics only are the enablers. The real matter is business, it\u2019s all about solving relevant and high impact business problems. Whatever role you play in the analytics value chain, you need to think like a business user. Only then will you be able to structure the right problem for a solution and eventually create significant business value. Your success should be measured not by the complexity of your statistics or cutting-edge technology, but by what business impact you were able to drive. Analytics is here not only to answer questions asked by the business leaders but also to ask newer business problems and drive business performance from the front.