how to successfully exploit big data for business advantage

1. How to Successfully Exploit Big Data for Business Advantage Bill Schmarzo, CTO EMC Consulting Julie Lockner, Senior Analyst and VP of Data Management Enterprise Strategy Group Copyright 2011 EMC Corporation. All rights reserved. 1

2. Agenda EMC Consulting Its a Whole New Big Data World The Big Data Opportunity Enterprise Strategy Group 2011 Data Analytics Research Priorities Challenges Drivers Take Action Q&A Copyright 2011 EMC Corporation. All rights reserved. 2

4. Big data analytics provides potential for more timely, morecomplete, more actionable business insights Todays Situation Big Data Analytics RamificationsLess than 10% of available Vast majority of available data, includingenterprise data external sourcesRearview mirror reports, Forward looking predictions withdashboards, and analysis recommendationsWeeks, months, or even quarters old Real-time or near real-timeIncomplete, inaccurate, and Correlated, high confidence, governeddisjointed data dataArchitectures and methods that take Vastly accelerated time to market6 to 18 months to exploit Copyright 2011 EMC Corporation. All rights reserved. 4

5. More than just data volume, smart big data strategies alsoconsider the velocity, variety, and complexity of information Social media Images Documents Sensor/ location-based Audio Text VideoWeb traffic Industry-specific Transactional: ERP, CRM, SCM, Smart Grid POS Gain new insights on Deliver to any customers, products, and device at any time operations Copyright 2011 EMC Corporation. All rights reserved. 5

6. The impacts to both the Business and IT are significant, and early adopters will fundamentally change their industries Business Impacts IT Impacts More agile, more real-time, more Enhanced user experience that accurate decision-making delivers insights to any device Predict and spot changes in Operationalization of data dynamic and volatile markets scientists and analytic insights Deeper understanding of Tools and processes for data customer preferences and quality, governance, and security behavior Cloud for self-service, Greater fidelity in risk assessment collaboration, agility, and cost and compliance enforcement reduction Through 2015, organizations integrating high value, diverse new information sources and types into a coherent information management infrastructure will outperform industry peers financially by more than 20%Source: "The New Value Integrator," Insights from the Global Chief Financial Officers Study Copyright 2011 EMC Corporation. All rights reserved. 6

8. With big data, leading companies are making forward-looking decisions about customers, products, and operations using all available data in real time with complete data confidence Telco Insurance Healthcare Payer Social Media Site Analysis across entire Calculate catastrophic Integrate and analyze Capture and analyze customer set risk at household vs. patient demographics PBs of unstructured generated a social zip code level and treatment data to and structured data network graph based Optimize hurricane consolidate data silos Time to market new on calling patterns policy pricing and and detect potential features reduced from Within 2 weeks renewal decisions for fraud in real-time vs. 2-3 weekly to daily identified customers specific coastal area weeks after claim A/B testing changed who were 7x more households at the authorization UEX which increased likely to change policy level to reduce Enabled faster decisions time spent on site providers book of business risk in fraud detection for 50% and increased evidence-based specialty game revenue 3x care Copyright 2011 EMC Corporation. All rights reserved. 8

9. TM Enterprise Strategy Group | Getting to the bigger truth. ESG Research 2011 Data Analytics Research Data October 2011 Julie Lockner, Senior Analyst and VP of Data Management Enterprise Strategy Group2011 Enterprise Strategy Group

10. Data Growth Is the Top Database Challenge In general, which of the following challenges does your organization have with its current database environment and supporting infrastructure? Which would you characterize as the primary challenge for your organization? (Percent of respondents, N=270) Managing data growth and database size 19% 51% Keeping up with database performance requirements 15% 52% Maintaining security/compliance 15% 51% Deploying new database technology platforms 11% 31% Primary 9% database Lack of skilled staff 28% challenge Supporting databases in virtualized environments 7% 31% All database Patch & maintenance processes 6% 36% challenges Keeping up with current version of supported database release 4% 34% Creating test/development environments 4% 27% Application data model knowledge transfer 4% 21% Provisioning storage 3% 27% Provisioning servers 1% 14% Other 1% 1% 0% 10% 20% 30% 40% 50% 60% 2011 Enterprise Strategy Group 10

11. Which Industries Have the Most Database Data? Total amount of database data, by industry. (Percent of respondents) 100 TB or more 10 TB to 99 TB Less than 10 TB Retail/Wholesale (N=24) 46% 25% 29% Financial (N=46) 43% 33% 24%Communications & Media (N=20) 40% 30% 30% Manufacturing (N=61) 33% 44% 23% Health Care (N=25) 20% 52% 28% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2011 Enterprise Strategy Group 11

12. Data Analytics Is a Top IT Priority for Many Organizations Relative to all of your organizations IT priorities over the next 12-18 months, how would you rate the importance of enhancing data analytics activities? (Percent of respondents, N=270) Dont know, 2% Our most important IT Not among our top 20 priority, 6% IT priorities, 5% One of our top 20 IT priorities, 15% One of our top 5 IT priorities, 45% One of our top 10 IT priorities, 27% 2011 Enterprise Strategy Group 12

13. Similar Challenges Plague Data Analytics Projects Which of the following data analytics challenges has your organization experienced? (Percent of respondents, N=270, multiple responses accepted) Data integration is complex 47% Lack of skills necessary to properly manage large data 34% sets and derive value from them Data set sizes limit our ability to perform analytics 29%Unable to complete analytics in a reasonable period of 28% time Current database license costs are too expensive 25% Current data analytics license costs are too expensive 21% Storage requirements are too expensive 21% 0% 10% 20% 30% 40% 50% 2011 Enterprise Strategy Group 13

14. What about Data Integration Challenges? Which of the following data integration challenges are currently facing your organization? (Percent of respondents, N=240, multiple responses accepted) Integration processes take too long 39% Data volumes are too large 35% It is difficult to add or integrate new data sources 29%Lack of process ownership due to disparate applications 28% Poor data quality inhibits proper data integration 27% Integrating data from cloud-based (i.e., SaaS) 21% applications Lack of adequate skills 20% Lack of adequate technology 18% We do not have data integration issues 4% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 2011 Enterprise Strategy Group 14

15. While Key Skills Are Sorely Lacking In which of the following areas of your database/data management environment does your organization have a shortage of skills? (Percent of respondents, N=75, multiple responses accepted) Database administrator 45% Data architect 45% Application developer 31%IT infrastructure (i.e., servers, storage, etc.) administrator 28% Enterprise architect 24% Business analyst 21% Data scientist 17% Application administrator 17% Server virtualization administrator 15% Data analyst 13% 0% 10% 20% 30% 40% 50% 2011 Enterprise Strategy Group 15

16. More than Half Are Processing at least TB at a Time! On average, approximately how much data is processed as part of a typical data analytics exercise? (Percent of respondents, N=270) 25% 23% Big Data Volume Zone 20% 17% 17% 17% 15% 10% 10% 7% 7% 5% 3% 1% 0% Less than 250 GB to 500 GB to 1 TB to 5 TB 6 TB to 10 11 TB to 25 26 TB to 50 More than Dont know 250 GB 499 GB 999 GB TB TB TB 50 TB 2011 Enterprise Strategy Group 16

17. Nearly Half Are Integrating Data from at least 4 Sources On average, how many data sources does your organization need to integrate in order to support data analytics activities (i.e., feeds to a data warehouse, business intelligence system, etc.)? (Percent of respondents, N=252)40% 38% Big Data Variety Zone35%30%25% 20%20% 17%15% 12%10% 8% 5%5%0% We typically We typically We typically We typically We typically Dont know integrate from 2 integrate from 3 integrate from 4 integrate from 5 integrate from unique data unique data unique data unique data more than 5 sources sources sources sources unique data sources 2011 Enterprise Strategy Group 17

18. More than Half Update Data in Real-time or Near Real-time How frequently is data typically added and/or updated during the integration process? (Percent of respondents, N=240) Big Data Velocity Zone 40% 38% 36% 35% 30% 25% 20% 15% 15% 10% 6% 5% 3% 2% 0% Real-time Near real-time Batch daily Batch weekly Batch monthly Batch (within a day) intermittently 2011 Enterprise Strategy Group 18

19. Top Five Drivers for Evaluating New Data Analytics Solutions What requirements are driving your organization to evaluate new data analytics solutions? (Percent of respondents, N=102, three responses accepted) Cost reduction of existing platforms 27% Current data analytics solution(s) does not meet 26% requirements/needs Organization is moving towards more real-time 25% analyticsNew application deployments and/or upgrades placed a 25% new strain on current data management solutions New business processes have generated new data that 23% needs to be analyzed 21% 22% 23% 24% 25% 26% 27% 28% 2011 Enterprise Strategy Group 19

20. Expected Benefits of Big Data Analytics Which of the following benefits does your organization expect to derive from deploying a new data analytics solution? (Percent of respondents, N=102, multiple responses accepted) Improved business agility 55%Ability to complete analytics in a shorter period of time 44% Easier to manage 43% Ability to complete analytics on larger data sets 34% Reduced deployment time and cost 34% Ability to leverage existing resources (i.e., staff) 30% Reduced infrastructure costs 26% Simplified data integration 26% Ability to accommodate new data types 22% 0% 10% 20% 30% 40% 50% 60% 2011 Enterprise Strategy Group 20

21. ESG Recommends Learning from Experienced Experts Data analytics is a top IT priority Challenges are only compounded by more data volumes and demand for faster results, as well as more data variety and complex integration challenges Leverage hired experts to augment your team Big Data requires new techniques and technologies to harness value Incorporate a train-the-trainer regiment in the methodology Build a plan that can accommodate future change Leverage experience to look beyond todays challenges 2011 Enterprise Strategy Group 21

23. Big Data Advisory Service: find the right big data business opportunity and build a comprehensive plan/roadmap 1 Pick the best- fit, priority business opportunity Copyright 2011 EMC Corporation. All rights reserved. 23

24. Big Data Advisory Service: find the right big data business opportunity and build a comprehensive plan/roadmap 2 Build use cases that drive next generation BI and analytics 1 3 Create a conceptual architecture for a more agile data platform Pick the best- fit, priority business opportunity Assess readiness of data quality, 4 governance, and security 5 Develop a vision for applying cloud capabilities Copyright 2011 EMC Corporation. All rights reserved. 24

25. Big Data Advisory Service: find the right big data business opportunity and build a comprehensive plan/roadmap 2 Build use cases that drive next generation BI and analytics 1 6 3 Create a conceptual architecture for a more agile data platform Pick the best- Integrate fit, priority findings into a business phased opportunity Assess readiness of data quality, roadmap 4 governance, and security 5 Develop a vision for applying cloud capabilities Copyright 2011 EMC Corporation. All rights reserved. 25

27. Next Steps Contact us today for a follow up call or visit Bill Schmarzo [email protected] Julie Lockner 508.377.3410 [email protected] Read our blogs http://www.enterprisestrategygroup.com/bigger-data/ http://infocus.emc.com Download our white papers Big Data Analytics: Gain Competitive Advantage from the Combination of Big Data and Advanced Analytics http://www.emc.com/collateral/emc- perspective/h8668-ep-cloud-big-data-analytics.pdf ESG Big Data Advisory http://www.emc.com/collateral/analyst- reports/esg-emc-consulting-big-data-advisory.pdf Copyright 2011 EMC Corporation. All rights reserved. 27

how to successfully exploit big data for business advantage

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