NASSCOM Big Data &#038; Analytics Summit 2014 &#8211; Industrialization of Big Data
The vast proliferation of data and the pressing need to stay one step ahead of the competition has sharpened focus on using analytics within organizations. Analytics today has matured enough to be a language of boardrooms, the new yardstick for organizations to compete differently and businesses today are leaving no stone unturned to embrace this disruption to reinvent themselves and rethink business performance. Leaders today are building advanced-analytics capabilities for predicting and optimizing outcomes, with Analytics at the very core of how they do business, helping them to supersede newer thresholds to succeed in this cut-throat marketplace. Only a chosen few who have successfully decoded the context behind the data deluge are the ones who are strongly positioned to upturn the future and define new rules of sustaining in the game of “Survival of the Fittest”. Milliseconds count, especially in the world of real-time business ecosystem. This new phenomenon of Data-driven business models is enabling the creation of hyper-intelligent software platforms that address myriad issues, from sales to customer service to the design of personalized products to the fact-based management process, and building an organization that is more real-time and responsive to marketplace changes. Unarguably, Analytics has now become the de facto requirement in organizations with companies designating dedicated teams to ensure analytics pervasiveness is seamless and very much part of the organizational DNA. Whether you’re dealing with high-value customers, luring in new prospects with dynamic marketing efforts, or adjusting the wheels of your business on-the-fly, the need for agility & real-time decision making is widespread these days. Across industries big data and analytics has become a strategic imperative for most organizations as they compete both locally and globally. It helps them to rethink customer management right from acquisition, value enhancement to saturation and attrition; increase focus on proactive risk mitigation and ensure regulatory compliance; improve effectiveness while managing cost better. Analytics today has proven to be the crucial ingredient of success for organizations across industries, rehashing the key business dimensions which form the basis of competition: customer, risk and operations. Retail and e-commerce are two sectors that are using big data and analytics extensively to drive competitiveness by redefine shopping experience, building Smarter operations and better merchandising & supply network. BFSI is another sector that is a big adopter of big data analysis and has helped them in pricing services better, render hyper-personalized experience to customer and reduce Fraud & Abuse to a great extent. For life sciences & healthcare, analytics has been instrumental in analysing clinical data has helped identify early adverse reactions, predict development successes and avoid costly late-stage failures, optimize targeted therapies. The need to quickly adapt to the evolving market trends is particularly true for the extremely competitive and dynamic industry like telecom. Use of big data analysis has helped it to respond to manage subscriber churn better, devise customer-centric pricing plans, improve asset utilization and optimize related labour costs. The integrated data view has enabled the business impact across the customer life cycle, including customer identification, acquisition, relationship management, and retention and value enhancement. The IT industry has used analytics to drive efficiency, process compliance, improve sales pipeline and reduce cost. For Energy and Utilities industry, Analytics has been all about monitoring energy usage patterns and leveraging the insights to transform the grid from a rigid analog system to a dynamic and automated energy delivery system. A number of companies are also looking at analytics to drive innovation and transform business processes and operations. Companies leveraging big data and analytics to accelerate innovation and efficiency clearly illustrates that it has come a long way. While some sectors have taken the lead, others have realized its importance in long-term growth and surviving in a highly competitive environment. Dynamically changing customer trends will further drive the growth of analytics, compelling organizations across sectors to analyse how information can be used intelligently. NASSCOM’s 1st edition “Big Data Analytics – A Big Fish” was centred on capturing the essence of Analytics and demystifying how businesses could overcome the challenges and implement big data analytics. The 2nd edition of Big Data and Analytics Summit 2014,”Industrialization of Analytics” shall primarily be focussing on what it takes to build an Analytically-mature organization with analytics embedded at the business core & across the business value chain, how brand India as the next big “global hub” for Analytics & Big Data, thought leadership in the field of Analytics, share best practices on processes, tools, technology, technique and applications used in the context of analytics and also brainstorm upon how to build India’s Analytics talent strength. Join us for the 2nd edition of the NASSCOM Big Data and Analytics Summit 2014, Hotel Trident, Hyderabad on 27th June, 2014. Time’s ripe to build business for the future driven by facts, powered by Analytics & Big Data!
The vast proliferation of data and the pressing need to stay one step ahead of the competition has sharpened focus on using analytics within organizations. Analytics today has matured enough to be a language of boardrooms, the new yardstick for organizations to compete differently and businesses today are leaving no stone unturned to embrace this […]
The vast proliferation of data and the pressing need to stay one step ahead of the competition has sharpened focus on using analytics within
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["big data", "API", "AI", "data-driven", "ML", "innovation", "RAG", "analytics", "GAN", "R"]
["AI", "ML", "analytics", "RAG", "R", "API", "big data", "GAN", "data-driven", "innovation"]
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