Covering Disruptive Technology Powering Business in The Digital Age

The universal availability and applicability of the internet, and rapidly progressing technology tools, have digitised our daily life to a large extent. Whether we are searching for a restaurant, booking an air ticket, making a bank transaction, or sharing experiences with friends and family, we just cannot escape digitisation. To support this ubiquitous adoption of the internet in our daily life, corporations have understood the need for mining the flood of data—that they have access to—to understand their customers, and serve their needs and wishes accurately, thus earning their loyalty and creating significant business value. Mining and drawing valuable conclusions from data falls under the new domain of Data Analytics.

Data is increasingly being called the new ‘gold’, and with good reason. Cut-throat competitiveness in each and every market segment means that industry survival is directly correlated to effectiveness of Big Data mining. Consider how Netflix has successfully segmented its users into over 70,000 profile types to drive its brand proposition. Or Macy’s, which employed Big Data Analytics to boost its holiday sales by 49% last season. Socially-enabled business processes, mobility, Data Analytics and cloud computing (SMAC) are reshaping the way companies have relied on technology for doing business. Their expectation is that their technology partners will offer intelligent solutions and skills in the analytics space. Software service providers are making big investments, including having more data scientists who can sift through huge stacks of data. While local service providers like Infosys and Wipro are lagging a bit, US firms like Accenture are reporting 25% of their $30 billion revenue coming from SMAC engagements. Clearly, Data Analytics has become the growth engine for IT industry.

However, just like gold, oil and other precious commodities, data has to be refined to unlock this immense value trapped within it. This is where data scientists come in. These professionals help businesses identify the worth of their data and outline a detailed strategy to optimally utilise this wealth of information. From software giants such as HP, Microsoft, Dell, SAP, Oracle, IBM and EMC, to highly specialised analytics firms such as KPMG, Deloitte and McKinsey, to e-commerce giants such as eBay, businesses big or small the world over are investing in Big Data to fully exploit the value that data can add to their operations. Even indigenous IT service providers such as Infosys and TCS have identified the growing demand for Big Data, and are now investing in setting up specialised practices for data management and analytics.

Needless to say, the demand for software professionals with Big Data experience has sky-rocketed. Industry estimates indicate that the demand for data professionals increased by 90% both in 2014 and in 2015; in comparison, software application developers saw only a 50% growth in their job opportunities. As such, many companies are now investing into creating infrastructure for Big Data analysis, and are looking to build a strong team of skilled data scientists. Another factor that makes the Big Data industry lucrative is the pay package on offer—data scientists are often paid 30-40% more than the median salary in the software industry, while yearly remunerations in excess of Rs 1 crore are being offered to leadership roles in this domain.

Lucrative financial payouts are not the only draw to the Big Data industry. The ‘hiring scale’—which measures the difficulty levels faced by employers in finding the right applicants—is the highest for Big Data skills. This means the requirement for Big Data analysts is only set to grow in the future.

Since it is an emerging area, it offers infinite opportunities for innovation—creation of new models to provide deeper insight into customer behaviour, ability to launch targeted marketing campaigns, optimising supply chains, reducing equipment maintenance costs, managing risk, etc.

Professional/technical services and IT are the leading industries with the maximum demand for Big Data professionals, while industries such as manufacturing, retail trade, financial services and healthcare have also seen rapid adoption of Big Data technologies. Business functions such as marketing, sales, risk management and manufacturing are seeing broadbased demand. Marketing, in particular, has seen the maximum growth for Big Data technologies, owing to the greater business impact generated—the demand for data scientists witnessed a growth of 60% in the marketing function alone.

While Big Data offers exponential growth opportunities, aspirants planning on pursuing a career in the domain must recognise that the field is very competitive, as it attracts the best brains in the industry. The skillset required for success is quite demanding. There are chances of failure too. One must have an analytical and creative mind, an understanding of difficult topics like machine learning and quantitative reasoning, a degree in mathematical sciences, and substantial knowledge of programming languages such as R, Python, C++ and SQL.

This article was originally published on www.financialexpress.com and can be viewed in full

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