The Canadian Realities of Big Data and Business Analytics. Utsav Arora February 12, 2014

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1 The Canadian Realities of Big Data and Business Analytics Utsav Arora February 12, 2014

2 Things to think about for today How Important is Big Data for me? Why do I need to implement Big Data and Analytics technologies? What are my challenges when it comes to managing and analyzing data? Should I be evaluating new technologies when it comes to solving problems? 2

3 The Beginning of the Journey. Babbage had most of this system sketched out by 1837, but the first true computer to use this programmable architecture didn t appear for more than a hundred years. - Steven Johnson 3

4 The Technological Evolution Continues.. 4

5 What is Big Data? The Four V s New generation of technologies and architectures designed to economically extract value from very large volumes of a wide variety of data by enabling high-velocity capture, discovery, and/or analysis. 5

6 What is Big Data? The Four V s New generation of technologies and architectures designed to economically extract value from very large volumes of a wide variety of data by enabling high-velocity capture, discovery, and/or analysis. 6

7 What is Big Data? The Four V s Terabytes Data Volume Petabytes+ Structured Data Variety Unstructured Batch Data Velocity Streaming $ Value $$$$$ 7

8 Market Reality True Big Data Projects Big Data Inspired Projects 8

9 Performance Management and Analytic Applications Business Intelligence and Analytics Tools Spectrum of Applications Financial Performance and Strategy Management Applications CRM Analytic Applications Query, Reporting, and Analysis Tools Advanced and Predictive Analytics Tools Supply Chain Analytic Applications Services Operations Analytic Applications Content Analytics Tools Spatial Information Analytics Tools Workforce Analytic Applications Production Planning Analytic Applications Data Warehouse Management Platforms Data Warehouse Management Data Warehouse Generation 9

10 Canadian Big Data and Business Analytics Forecast Software revenues are forecasted to grow to C$1.53B by 2016 End User Query, Reporting and Analysis Software Advanced Analytics Data Warehouse Generation CRM Analytics IDC Canada Enterprise Applications Forecast, May

11 Big Data Helps Save Tigers Utilizing Data Analytics software to fight environmental crime in India. Analyzing unstructured data from investigations Build connections between isolated crimes and large scale enterprises Result: Improved law enforcement efforts and facilitated a 30% increase in India s tiger population 11

12 Big Data, IoT, and Telematic Devices Facilitating Usage Based Insurance Auto insurers are installing telematics devices in cars Telematic devices transmit data in real-time to insurers Volume of Data: 20 min commute = 1200 records of data / day 500,000 records per year per driver Result: Accurate pricing, risk management, and loss reduction through better claim assessments 12

13 Canadian Adoption of Big Data and Business Analytics Technologies 13

14 Adoption of Big Data and Business Analytics among Large Enterprises 7% 28% 65% Currently uses Not aware Does not use N=155, ITAP

15 Adoption of Big Data and Business Analytics Software by Vertical 70% Large data intensive businesses 60% 50% 40% 30% 20% 10% 0% Financial Services Telecom, Transport, and Utilities Public Sector Business and Personal Services, Retail, Wholesale and Distribution Manufacturing and Resources N=155, ITAP

16 What's Driving Growth in the Adoption of Big Data and Business Analytics Technologies? 16

17 The Intersection of Big Data and Analytics Within the Third Platform Social Business Mobility Big Data & Analytics Cloud 17

18 A Shift in Deployment Models Among Large Enterprises for Big Data and Analytics Software 70% On-Premise 19% Cloud Based 11% Outsourced and Managed Services N=102, ITAP

19 Drivers of Growth Dynamic and Competitive Business Environment Increased Digitization=Availability of Data Dynamic Regulatory Environment Human Capital Dynamics 19

20 Technology Opportunities What are you focusing on? IoT Analytics Rich media analytics Cognitive Computing Monetization of data Wearables Quantified Self 20

21 Use Case 1: IoT Analytics in Healthcare Kasier Permanente through its partnership with Microsoft is remotely monitoring patients by connecting to smart phones, blood pressure devices, glucose meters, etc. 21

22 Use Case 2: Wearables and Sports Analytics Managers of a soccer team are making substitutions by analyzing the fatigue levels of players through data received from smart watches 22

23 Key Challenges to Big Data Projects Skills shortage Alignment of objectives between business and IT Lack of strategy on deriving value from data Data consolidation and complexity 23

24 Overcoming Challenges Innovation is an evolutionary process, so it's not necessary to be radical all the time. Marc Jacobs 24

25 IDC Big Data Maturity Model: A Guide to Unlock Information Assets VISA now has the ability to drill down on hundreds of transaction attributes, such as average authorization volumes, average ticket sizes, and frequency of purchases, giving the network the chance to address $2 billion in potential incremental fraud before money is lost Recurring projects Project, process and program performance; standards emerge Continuous and coordinated process improvements Ad hoc project Opportunistic project deployments Enterprise wide, documented, accepted strategy ROI measured Trusted comprehensive, multi-sourced data sets Optimized software and hardware Executive priority Staffing, technology, funding exists IDC Visit us at IDC.com and follow us on 25

26 Final Thoughts Don t let the hype distract you Being a data driven organization will give you a competitive edge Domain expertise matters as much as IT expertise Consider analytics as a separate function i.e. Chief Data Officer/Chief Analytics Officer LOB and IT executives need to collaborate 26

27 Thank you! Utsav Arora Senior Analyst Enterprise 27

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