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Why enterprises will en-route India for big data analytics

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McKinsey estimates that India will need 200,000 data scientists in the coming years. While the demand is huge, organizations are facing acute challenges in training the workforce and making their skills relevant to their customer needs.

The big data analytics space is seeing unprecedented growth in volume, velocity and veracity of data. Research firm IDC has pegged the big data technology and services market growing at a compound annual growth rate(CAGR) of 23.1 percent from 2014-2019 with annual spending reaching $48.6 billion in 2019.

Amidst, India is coming in a limelight for investors, as there is a remarkable rise in VC investments in data analytics startups in India. Big data analytics sector in India is expected to witness eight-fold growth to reach $16 billion by 2025 from the current level of $2 billion, according to a report by National Association of Software and Services Companies (NASSCOM). The report also highlights that there is approximately $700 million worth of start-up funding over the last two-and-half years. Moreover, NASSCOM is setting up a Centre of Excellence for big data and IoT, and over one-third of the 1000 GICs in India are investing and moving their data analytics and big data work to India, in addition to engineering research and design.

McKinsey estimates that India will need 200,000 data scientists in the coming years. While the demand is huge, organizations are facing acute challenges in training the workforce and making their skills relevant to their customer needs. “Adoption of big data is increasing in India, and the country is becoming hot bed of analytics companies in terms of both talent and services available here. But, we are short of skilled data scientists and analytics professionals in the industry,” said Manish Mittal, Managing Principal & Country Head of India Global Delivery, Axtria Technologies. Axtria is a data analytics startup, which is aiming to fill the talent gap in India to create an ecosystem of data analytics, and to be knows as pioneer in the industry. The startup has established structured learning & development programme called Axtria Institute which addresses this issue and grooms talent for three months, immediately after hiring them.

While talking about CIOs demand from data analytics solution providers, Mittal told that CIOs are becoming business driven and are looking for customized solutions which can reduce capex and increase ROI for the business. To meet this demand, Axtria has a platform, SalesIQ to manage sales operations.

The company recently implemented this solution for a leading pharma company, which was facing issues like black-box approach and lack of user friendliness with the existing system. The client was seeking to manage end to end sales operations with an automated application. The client wanted a system for 1600+ sales representatives which supports optimized alignment of territories, efficient call plans for sales targeting and call plan feedback at both account and physician level which helps improve overall sales force effectiveness. Axtria team configured the SalesIQ call planning solution to integrate the call plan feedback application with key focus on user friendliness and usability aspects to reduce the training requirements. Various scenarios were created within the stipulated timelines and reviewed with the client to reach the optimized Call Plans for sales teams. Axtria also conducted training sessions for the district managers. The application configures by Axtria was accessible through various platforms such as iPad, iPhone, Android and through all web browsers. The pharma company was able to solve the business challenges and also achieve transparent approach and employees satisfaction in terms of ease of use and intuitive application.

Putting data analytics scenario in perspective with this use case, Mittal said all the verticals in India are now becoming data rich, hence India would be soon a great market for data analytics due to the availability of data and data scientists.

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