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The big shift

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Being prepared is the secret to making a successful career shift to Big Data

Sudeshna Datta

Better late than never" seems to be the best advice for those planning a late career shift to Big Data. First off, the benefits of making this much-needed switch are far too many to be ignored. A job in data analytics is being touted as the "dream job" and there are no limits to how fast this field is growing. There is also a high demand for data analysts and data engineers across segments looking to exploit the potential of Big Data to analyse and predict trends, patterns, human behaviour and find new correlations that can lead to better business decisions.

Before you decide to take the plunge, it will stand you in good stead if you're already prepared. Begin by brushing up your skills of using statistical software. Choose from SAS, SPSS/R and SQL - any should be fine, but aim at in-depth knowledge (with modules and techniques) instead of knowing a bit about all.

Once you're proficient in software, find a trusted teacher to learn the tricks of the trade. It pays to seek guidance from someone who's already excelling in the field or there are always self-help tutorials where you can learn from the professionals. There are a host of universities offering accredited programmes in data science and analytics along with institutes that have tied up with Big Data specialists in the industry. This time should take you closer to cracking the secret about what to take into account.

After picking up these basics, a data engineer needs to spot the right opportunity on the job. The aim of the data analyst here should be to get to the data source and it's likely that the numbers lend themselves to some statistical deductions that can benefit business processes. Begin by making small, but significant points in your business reports. Once you prove your worth in making a valuable contribution, the higher administration might trust you with more complex and confidential data. To ease into the process, it helps to draft a list of questions pertaining to customers, shareholders and the management to understand what it is that you are really seeking data for. Once you know the purpose of studying Big Data, you will be better equipped to measure its efficacy - if the analytics provide insights relevant to the questions, the project has been successful.

A career in Big Data, however, will never be a cakewalk. Since the field will require constant upgradation of skill sets, it's important that a candidate/employee remain up-to-date. Even though getting a grasp of fundamental concepts is fairly straightforward, the finer details are things that only come with experience. Another major drawback of a career in managing enormous amount of Big Data is the possibility of boredom.

Regardless of these challenges, Big Data is big business. Analytics are no longer restricted to IT and are being increasingly applied into research, strategy, product development and marketing. This creates more scope for a field that's still "emerging", allowing applicants to keep adding more value to the organisation they work for.

—The author is executive vice president and co-founder, Absolutdata

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