You're reading Entrepreneur India, an international franchise of Entrepreneur Media.
As markets become bigger and more cohesive, Big Data analysis seems to be the only way for organizations to make sense out of the terabytes of data. As a result, jobs in analytics and Big Data are sure to be some of the most desired opportunities in the coming years.
Data Scientists and analysts are supposed to serve the key role of acting as a bridge between multiple, disjointed data sets and baffled management who are looking for a few actionable insights out of this large haystack of data. This has heightened the demand for Big Data analysts in both top-rated and emerging firms today.
Mentioned below are a few factors that one should keep in mind while looking for a job in the area of data science and big data analytics:
Get a sound footing:
There is no substitute for having a solid understanding of the concepts. Do you know the difference between Descriptive, Predictive, and Prescriptive analytics? Do you know what ETL is, and how it differs from advanced analytics? How about Business Intelligence (BI) versus Data Science? Do you know what is supervised learning versus unsupervised learning, and which of the two buckets does a Fuzzy-K-Means model belong to? There are literally dozens of mathematical ways to develop an understanding of the data – and you’ll be able to use the right tool for the right job but only once you understand the basic concepts well.
If you haven’t already, get some basic education to round out your skill set. Buzzwords won’t get you far.
Master a particular tool:
The presence of many programs in Big Data such as SAS, SPSS, R, SQL etc. make the profession diversified. If a company internally uses the particular set of tools, getting a trained resource or an expert in one of them means they have to do less work to get you to be a productive employee.
Rather than have perfunctory knowledge of a dozen tools, if you can claim to have deeper experience with one or two of them, it increases your marketability as a resource. Now what you need to do is to search for an organizational fit.
You might have an inherent knack in creating and maintaining an analytical database and apply the tools/techniques to build models from it, but can you articulate the business value this can translate into? If you can connect the technology with the business value it delivers, you are in a sweet spot.
There is a huge demand for personnel who do not get intimidated by Big Data and are able to break them down into digestible nuggets to obtain and interpret such knowledge for the management.
Lately, it has been seen that people who are able to weave a story out of the data can easily convince the clients or the management to take necessary steps in the right direction for the company’s benefit.
Focus on the next industry vertical that will adopt analytics:
The 2011 movie Moneyball was based on the sabermetric approach which heralded a new age of statistically-driven sporting decisions. Similarly, there is enough scope for Big Data approaches such as weather analytics affecting grocery outputs, effect of an extra 20 seconds of call center wait time on customer satisfaction etc.
What you need to do is to think about a business where you are applying and showcase use cases from other industries that can be put to their benefit.
Different industry verticals will mature in their analytics thinking over time, but if you can anticipate the adoption curve of big data and analytics in new industries that are yet to adopt it, you can turn yourself into a thought leader and a first mover in those verticals.
Maintain a portfolio of your work:
What was the problem? What were the tools and techniques used? What unique insight were you able to gather? How was it put into use, and what was the business outcome (savings, new revenue generated, etc.)? As you work in different areas, it is important for you to be able to build a repertoire of case studies where you have seen analytics in action.
Gather all the facts around the use case, even if you were not involved in all pieces of the puzzle. It will give you an appreciation for the workflow around the application of analytics in a real business. These are examples that you can highlight on your CV, and also leverage during interview conversations.
The last two years have generated more amount of data than all previous years of recorded history combined! As a result, entire markets hinge on correct accumulation, classification, analysis and interpretation of big data. The analytics tool is what will determine the strategies of organizations in the future, and quite possibly play a significant part in the day-to-day life of an average person as well.
In such a scenario, a career in Big Data is probably one of the most lucrative options in the future, something that will help to control massive audiences through the strings of binary data.