A big data analytics project isn’t successful just because a system was built that can capture, store, run, and deliver analytical workloads. The business must deliver actionable insight that produces bottom line results. How do business owners and IT work together to identify the right problem and design the right architecture, to exploit these new data monetization opportunities? Register to view this recorded webcast and learn: How “big data” can be used to combine new, rich data sources in novel ways to discover business insights How to identify where and how big data analytics can be successfully deployed so that it will yield real business value How to ensure continued, sustainable success with a big data project How to embark on a big data journey with a solid plan in place
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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
3. Its a Whole New Big Data World EMC Consulting Copyright 2011
EMC Corporation. All rights reserved. 3
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
7. The Big DataOpportunity Copyright 2011 EMC Corporation. All
rights reserved. 7
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
22. Take Purposeful Action on the Big DataImperative Copyright
2011 EMC Corporation. All rights reserved. 22
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
26. Q&A Copyright 2011 EMC Corporation. All rights
reserved. 26
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
28. THANK YOU Copyright 2011 EMC Corporation. All rights
reserved. 28