Over the last decade, businesses have undergone tremendous transformation. Today’s dynamic business landscape has given rise to continuously shifting business problems such as How to assess changing customer preferences? Who should be the target customer segment? What is the right pricing model that needs to be adopted for different product variants?
To address these problems, organisations across verticals are relying on the latest information available to infer and learn from, before taking a decision.
This trend has been enhanced by the data age, where organisations are progressively looking to leverage data and institutionalise data driven decision making.
With companies churning out a large volume of transactional data, capturing trillions of bytes of information about their customers, suppliers, and operations, the amount of data in our world has been exploding. In addition, social media websites, smartphones, consumer devices, multimedia content are also playing a key role in the exponential growth of big data volume.
Today, more and more firms are finding an edge, or a new niche, through their ability to extrapolate insights from data. Analysis of these vast datasets by various businesses is already creating a transformative impact across multiple sectors and is beginning to demonstrate that sophisticated analytical capabilities can result in great competitive advantage.
Ironically, even with such vast data available, its true value has not been fully unleashed. The availability of relevant talent especially people with expertise in statistics and machine learning together with managers and analysts who know how to obtain and use insights from big data is a critical constraint in realizing the benefits of big data analytics. Therefore availability of talent is the biggest constraint in the growth of analytics. The US alone is currently witnessing a shortage of analytics professionals which is expected to reach 180,000 by 2018. Nevertheless, the analytics industry continues to grow rapidly by leveraging skillsets existing in other industries and functions, and through offshoring.
Though US remains the largest market and leading talent provider of big data analytics, growing talent shortage has allowed India and China to emerge as a key offshoring destination for analytics services due to its large, low-cost talent pool in big data analytics. As of 2013, over 80 percent of the big data talent is concentrated in US, China and India, with the future growth of big data talent expected to come from India and China. With more students opting for higher education, big data and related sill sets talent in India and China is expected to surpass the US by 2030 with comparable quality, greater scalability, and lower costs. As per our estimates, China and India together are expected to incrementally add 6 times as many Big Data professionals as the US by 2030.
Big Data Talent Hotspots
The following global locations are the talent hotspots for Big Data:-
San Francisco Bay Area: Despite high talent cost, San Francisco Bay Area is expected to be the premier destination for Big Data and Analytics talent. The High Tech ecosystem provides a favorable setting for the development and advancement of new skillsets such as Big Data. The installed talent pool is spread across Multinational Corporations, promising startups and top universities present in the region. The Bay area is home to Big Data teams of reputed global firms like Google, Amazon, Yahoo, Apple, LinkedIn and Facebook. The applications of Big Data Technologies in these firms are wide ranging. EBay.com uses two data warehouses at 7.5 petabytes and 40PB as well as a 40PB Hadoop cluster for search, consumer recommendations, and merchandising. Walmart handles more than 1 million customer transactions every hour, which are imported into databases estimated to contain more than 2.5 petabytes (2560 terabytes) of data – the equivalent of 167 times the information contained in all the books in the US Library of Congress.
The presence of premier research institutions such as Stanford and University of California ensure a steady supply of qualified graduate engineers. They offer intensive programs in the field of Big Data research. Bay area is also a cradle for new age Big Data startups such as Platfora and Adchemy.
Bangalore: By 2020, Bangalore is expected to emerge as the second largest destination for Big Data R&D, driven by its fast growing and cost effective talent pool. MNCs such as Amazon, IBM, EMC and E-bay have big data teams operating from Bangalore. Local companies such as TCS, Wipro and Infosys are also building Big Data capabilities to cater to their international clientele.
Indian Institute of Science situated at Bangalore is a premier institute involved in cutting edge research in the field of statistics and analytics. In addition, the presence of startups is enriching the big data ecosystem. Inmobi, a mobile advertisement platform headquartered in Bangalore is building digital solutions for global customers using Big Data. Mu-Sigma Analytics recently valued at over a billion dollars * has built significant analytical capabilities and employs a large number of decision scientists and data scientists.
Beijing: Beijing is home to a sizeable, economical and fast growing Big Data R&D Talent pool mainly deployed across MNCs and large local companies present in the region. Beijing is expected to emerge as an attractive destination for Big Data R&D activities propelled by its fast growing and cost effective talent pool. MNCs such as Yahoo and IBM are working on Big Data in a small but significant capacity. IBM’s Beijing center focuses on deploying Big Data Solutions locally. Large local companies such as Baidu, Tencent and Alibaba are working on Big Data applications to unlock business value. The presence of research institutions such as Tsinghua University and the Chinese Academy of Sciences fosters the local ecosystem.
Shanghai: Shanghai is still in its nascent stages as a Big Data R&D hot spot, but is expected to grow rapidly driven by talent and cost benefits. MNCs such as eBay, IBM, HP and Intel have small Big Data teams working on Big Data platforms. Baidu is the primary local player leveraging Big Data capabilities out of Shanghai. Big data adoption in startups is still in the early stages. There are very few significant start-ups in this domain. The Shanghai Jiao Tong University houses researchers in the nascent stage of big data projects.
Kiev: Kiev is home to a sizeable and competent Big Data talent pool, which is currently being used for both Big Data R&D as well as deployment services. Kiev’s emergence as hub for big data talent will be driven by low cost and well educated talent pool. MNCs such as EPAM have setup centers in Kiev for Big Data R&D. Companies such as Ciklum and SoftServe are working on Big Data applications out of Kiev. Kiev lacks significant Big Data R&D led by universities and startups operational in Big Data segment.
To conclude with business becoming increasingly competitive, it has become essential for companies to adopt to change whether technological or obtaining the right talent. Therefore, for leveraging the full value of big data, companies need to have right talent on-board.