As Big Data has captured attention as one of “the next big things” in enterprise IT, most of the spotlight has focused on early adopters. But what is the state of Big Data adoption across the enterprise mainstream? Ovum recently surveyed 150 global organizations in a variety of vertical industries with revenue of $500 million+ and manage large enterprise data warehouses. We will share the findings from the research in this session. We will reveal similarities in awareness, readiness, and business drivers when compared to early data warehousing adoption back in the mid 1990s. We will discuss how early experience with emergence of the data warehousing adoption can provide a roadmap for proceeding with Big Data implementations in the next 2-5 years.

1. The State of Big Data Adoption in the Enterprise Tony Baer [email_address] November 2011

3. Survey sample by region Europe North America APAC 27% 33% 40% Sample size = 150 organizations Minimum > 1+ TByte data in enterprise DWs/analytic data stores

4. Company size & IT budget <$10m Don't Know $50m+ $10m - $50m 9% 7% 7% 77% Annual IT budget $50m - $250m <$10m >$1bn 22% 18% 17% 21% 22% Company size Big data is not limited to big companies! $250m -$1b $10m - $50m

5. Survey sample by vertical industry Other Media & Entertainment Mfg Public sector (government) ICT Healthcare Financial services Retail 5% 16% 13% 5% 21% 20% 5% 9% Transportation 6%

7. Mean analytic data store size Number of respondents 1 150 1000 3TB = mean 75 3000 5000 7000 Terabytes 2000 4000 6000 8000

8. Analytic data store size by data type 0% 10% 20% 30% No unstructured data 1 - 5 TBytes 5 - 10 TBytes 10 - 20 TBytes 20 - 50 TBytes 50 - 100 TBytes 100 - 500 TBytes 500 - 1000 Tbtyes Over 1000 TBytes Structured data Unstructured/ Variably structured data

9. Popular analytic data types 0% 30% 60% 90% B2B transactional Supply Chain Mgmt Call Detail Records (CDRs) Internet search indices Legal/regulatory documentation Legacy Apps CRM ERP Email/Messaging Currently Planned

10. Variably structured data – current & future demand Weighted score Social Media Web Logs Sensory Graph Rich media Text Time series All sectors Financial Svcs Healthcare Retail Public Sector Healthcare Healthcare Healthcare Healthcare FS FS Retail Retail Healthcare Public Sector FS FS FS Healthcare

12. Business objectives Big Data analytic projects change the analytics, but not the objectives 0% 30% 60% Other Advanced analytics Competitive positioning Business agility Regulatory compliance ID hidden business trends Predictive analytic insights Business forecasting Customer service Strategic decision making Operational decision making

13. Business sponsors The players are currently the same 0% 30% 60% Supply chain Other Customer management Internal operations Sales and marketing Finance

14. Advanced SQL analytic database use A 5-year head start on NoSQL 0% 2% 4% 6% 8% 10% 12% Oracle Exadata Sybase IQ Aster Data IBM Netezza Sand Greenplum Kognitio Teradata ParAccel Vertica Infobright

15. NoSQL platform use Considering Testing/ Evaluating In Production 0% 2% 4% 6% 8% 10% 12% Amazon SimpleDB Hadoop MongoDB Membase Cassandra CouchDB

16. Non-SQL languages/frameworks for analytic queries 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Java None PHP C or C++ Other language Perl Other framework/technology? Python Ruby MapReduce Now Future

17. Big Data in the cloud? No Yes Considering in next 12 months Considering in next 12 - 36 months 24% 9% 9% 58%

18. Technical concerns Analytic/NoSQL databases technology immaturity Current DW investments not easily extended In-house analytic skills Increased capital investment Visualizing large datasets Technology infrastructure costs Analysis requires additional IT resources Data integration complexity Systems & network performance impact High data volatility/refresh cycles Information filtering technology Data storage issues & costs Performance issues & query response times Data quality & governance Not Important Important

20. Who will deliver Big Data technologies & solutions? Plenty of room for new blood 0% 20% 40% 60% Existing data warehousing/ BI analytics supplier In-house Systems integrator Specialist provider Other technology provider

21. Big Data IT budget plans Based on 25% of respondents provided actual numbers Current IT budget Next year's IT budget Next 2 - 5 yrs Under $100,000 $100,000 - $1 million 1 - 5 million Over $5 million

22. Big Data budget plans 0% 10% 20% 30% 40% 27% 33% 44% Current IT budget Next year's IT budget In next 2 - 5 years Proportion of respondents

23. Thank you – any questions? Tony Baer Email: [email_address] Twitter: @TonyBaer All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher, Ovum (an Informa business). The facts of this report are believed to be correct at the time of publication but cannot be guaranteed. Please note that the findings, conclusions and recommendations that Ovum delivers will be based on information gathered in good faith from both primary and secondary sources, whose accuracy we are not always in a position to guarantee. As such Ovum can accept no liability whatever for actions taken based on any information that may subsequently prove to be incorrect.