In the last decade people have been calling Data sexy and Big Data, well they are calling it a mind-blowing phenomenon that is fast changing the way we live and work. It is one of the fascinating evolution of the 21st century, and it has revolutionized the tech industry in ways we could not have imagined. It is said that the digital universe is doubling every two years, and will reach 40,000 Exabytes (40 trillion gigabytes) by 2020. It is also said that if we take all the data we have and place it on CDs and they were stacked up, it would form five separate piles that would all reach the moon. Impressive, isn’t it?
Big Data has four dimensions: volume, variety, velocity, and veracity. It can be explained as a collection of structured and unstructured data, from traditional and nontraditional sources, too large and complex to process using on-hand, more traditional database management tools and applications.
As Big Data evolved, it became more about what organizations were doing with this data. It encompassed the insights derived from this humongous (Volume) data, which could often be untrustworthy (Veracity), come from varied sources in varied formats (Variety) and could evolve, transform, and exceed current processing capacity (Velocity).
The power of Big Data lies in the weight of its insights; insights that have the potential to transform businesses, and offer new and interesting solutions to deal with social and economic problems.
Today Big Data is considered a huge untapped source of profit that can keep competition at bay and attract better customers. Organizations are using Big Data to make smarter, faster, and more impactful decisions by focusing on value-generating efforts and capabilities. An effective Big Data strategy integrates and services various business functions and helps increase revenues, reduce risks, and bring down costs. Just having Big Data is not a sufficient criterion for success, however; enterprises also need to implement analytics effectively, to be able to garner insights that help improve profitability.
Today so many well-known names like Amazon, Alibaba, Google, Twitter, Facebook, and LinkedIn are using Big Data successfully, as are smaller companies and start-ups, to gain insights and improve profitability. In fact, so many businesses across every industry are using Big Data to make better business decisions. Big Data allows businesses to bring together both online and offline data along with transaction information, to better understand and service customers. The financial services sector is using Big Data to improve customer satisfaction, while also using it to combat fraud in a big way. The telecommunications industry, as it expands and grows, is also becoming heavily reliant on Big Data to gain more market share, and increase profit margins. Big Data helps them not only provide better customer service but also offers insights about innovative product services and segmentation techniques, that allow for strategies that generate new sources of revenue.
Let’s find out more about how a few of the more popular and better-known industries are harnessing Big Data.
Banking: Banks are using Big Data to improve customer service, find new customers, minimize fraud, and maintain regulatory compliance. However, to really be at the top of their game, smart banks are using Big Data along with advanced analytics to sharpen risk assessment and drive revenue.
Telecommunications: Like other sectors, communications service providers all over the globe are witnessing significant data growth due to the increased adoption of smartphones, the rise of social media and the growth of mobile networks. Many of these firms are tackling Big Data challenges to gain more market share and increase profit margins. Big Data can help service providers achieve some of the key business objectives – provide better customer service with the help of internal and external data, implement innovative product services using segmentation techniques, and develop strategies to generate new sources of revenue.
Retail: One of the early adopters of Big Data, the retail industry has been revolutionized by data and advanced analytics. Recommendation engines, Customer Relationship Building, Path to Purchase and Price Optimization are just some of the ways retail businesses are harnessing Big Data.
Education: New technologies related to Big Data allow education establishments to analyze everything from student behaviour, curriculum, at-risk students, and student progress, as well as implement a better system for evaluation and support of teachers and principals. Big Data implementations can also help improve student results, create customized programs, and improve the learning experience.
Government: Big Data enables governments to make an impact at local, national, and global levels. From managing utilities to dealing with traffic congestion or making healthcare better and more accessible, Big Data enables governments to utilize their resources efficiently and effectively while also improving the quality of life.
Health Care: Big Data is causing a revolution in healthcare, enabling better services at lower costs. Crunching health data can result in insights that can predict epidemics, avoid preventable deaths, better maintain patient records, and streamline treatment plans.
Manufacturing: The manufacturing industry has been able to use Big Data to improve both quality of products as well as process efficiencies, while at the same time also minimizing waste, thus enabling them to stay competitive in what can be a very volatile market. Smart manufacturing businesses, by enabling a data culture have been able to find better solutions to problems faster, thus impacting profits hugely.
The International Data Corporation (IDC) predicts that the Big Data analytics market will reach USD 187 billion by 2019 and grow to more than USD 200 billion by 2020, at a compounded annual growth rate of 11.7%. They also forecast a 50% increase in revenues from the sale of Big Data and business analytics software, hardware and services by 2019. Services are slated to remain the biggest players, claiming the largest chunk of revenue, with the banking and manufacturing industries predicted to be the ones who spend the most on Big Data initiatives. There is little doubt that Big Data and analytics will soon significantly impact just about every industry across the world.
As the Big Data industry grows, so does the demand for Big Data talent. Companies are willing to pay big bucks to draw the best skilled Big Data professionals. These high salaries are a result of demand being far greater than supply; in just the start-up arena, it is estimated that over 30,000 analytics and Big Data jobs are created each year across India.
Big Data Analysts get paid an average of Rs. 9.93 lacs per annum, and if they club it with Machine Learning skills, they bag a cool Rs. 13.94 lacs per annum on average.
People with full-stack knowledge of Big Data, not just Hadoop are currently in high demand. Hadoop, in combination with Spark and Tableau, along with knowledge of popular databases like Mongo and Cassandra, will make for that rare Big Data Unicorn.
A Big Data analyst would primarily be responsible for:
If you are thinking of a career in Big Data, you need to invest in the skills that Big Data recruiters are looking for in candidates. Essentially Big Data professionals need both programming and analytical skills. They also need a relevant domain as well as business knowledge and great communication and persuasion skills. And finally, what also goes a long way is being well versed in information/technology management. Of course, as important are the intrinsic skills like an analytic mindset, being proactive, intuitive, and having good interpersonal skills.
Let’s understand some of the key skills a little better:
If you are convinced that your future lies in Big Data, then you need to invest in obtaining some Big Data technical skills at the earliest. Take the time to investigate all the Big Data Training options available and choose one that best suits your learning as well as personal needs. You might choose to start with the many free MOOCs available or dive straight into a deeper certification program or even a master’s program (part time, full time or even advanced online degree programs).
However here is a tip- even before you complete a certified course or program, you can build your skills by being proactive and spending time on extra projects either at work or in your own time. Access a data set and perform a little analysis on it, contribute to open source projects or take part in data hackathons. Try to find ways to integrate Big Data into the current work you perform. Not only will it build your skills, but you will also impress your current employer. Also take time stay in touch with the industry and keep abreast of innovations in the Big Data world. Read books on Big Data, follow experts and blogs on Big Data and participate in competitions. The more knowledge you gain, the bigger the edge you will have.
Now you have understood quite comprehensively the skills that are needed to begin a career in Big Data and can hopefully truly comprehend the exact role of a Big Data professional. You also have a fair idea of how you can get the skills you need. So, are you are convinced it is the right career for you. If not, then here is a reminder of the key reasons why a career in Big Data is the way to go: