The world around us is changing. Data is embedded in everything, and users from all lines of business want to leverage this data to influence decisions. The trick is to create a culture for pervasive analytics and empower the business to use data everywhere. The core enabling technology to make this happen is Apache Hadoop. By leveraging Hadoop, organizations of all sizes and across all industries are making business models more predictable, and creating significant competitive advantages using big data. Join Cloudera and Forrester to learn: - What we mean by pervasive analytics, how it impacts your organization, and how to get started - How leading organizations are using pervasive analytics for competitive advantage - How Cloudera’s extensive partner ecosystem complements your strategy, helping deliver results faster

1. The Value of
Pervasive
Analytics
November 6, 2014
Mike Gualtieri – Forrester
Clarke Patterson - Cloudera

2. Pervasive Analytics Drives
Ultimate Value From Big Data
Mike Gualtieri, Principal Analyst
November 6, 2014

3. Executives and technology decision-makers
are remembering the power of data.
Please rank the following technologies according to their
importance and investment within your firm?
7%
24%
20%
18%
15%
16%
5%
16%
17%
18%
12%
33%
Data related projects
Systems of record applications
Systems of engagement applications
Cloud related projects
Mobile related projects
Social related projects
2nd Priority
Top Priority
Source: Forrsights Software Survey, Q4 2013, Base: 2,074 IT executives and technology decision-makers
© 2013 Forrester Research, Inc. Reproduction Prohibited 3

4. Why?
Meet business demand for analytics of all kinds.

5. It’s simple and self-evident: data is the fuel for insight
that makes your business engine run.
© 2012 Forrester Research, Inc. Reproduction Prohibited
5
Research &
Development
Operations
Marketing &
Advertising
Sales
Execution
Customer
Experience
Finance

6. #Analytics

7. Businesses often think of analytics as a set of
historical reports and dashboards…

8. Future
History
…but, analytics is also about the future.

9. Momentum is strongest for streaming and predictive
analytics, but underadopted.
“What is your firm's/business unit's current use of the following technologies?”
13%
10%
24%
21%
20%
18%
20%
16%
21%
33%
29%
37%
57%
54%
50%
49%
58%
56%
81%
15%
21%
27%
32%
19%
33%
42%
35%
50%
59%
77%
Reporting
Dashboard
Web Analytics
Performance analytics
Embedded Analytics
Olap
Process Analytics
Location Analytics
Search/Interactive Discovery
Predictive Analytics
Metadata Generated Analytics
Text Analytics
Advanced Visualization
Streaming Analytics
Non Modeled Data Exploration And Discovery
2014
2012
Source: Forrester Research
+52%
+62%

10. Most want deeper insights through advanced analytics
but familar challenges persist.
What are the main business and technical requirements or inadequacies of earlier-generation business
intelligence technologies that lead you to consider new BI techniques and technologies?
2%
2%
We want deeper insights through advanced analytics
Data volumes have grown beyond what we can cost-effectively manage
Data changes or becomes available much faster than we can process in
support of business decisions
We want to access data that was not accessible for us with existing
technologies
We don't know what our entire data universe contains, we need new ways
to explore data and discover patterns and insights
The performance of certain analysis is not sufficient
Analysis requirements change too fast to keep up with
The number of data formats that we must be able to deal with exceeds our
ability to cost-effectively integrate
The velocity of data is too high for earlier technologies
Earlier-generation technology is too expensive
Other (please specify)
Base: 452 North American technology decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
16%
20%
27%
28%
29%
28%
31%
33%
32%
32%
31%
35%
34%
26%
23%
35%
Business decision makers
Technology decision makers
Base: 249 North American business decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
44%
45%
12%
14%
© 2013 Forrester Research, Inc. Reproduction Prohibited 10

11. Quiz
What percentage of enterprise data do firms
use for analytics?
A. 12%
B. 34%
C. 53%
D. 76%
Enterprise
Data
© 2013 Forrester Research, Inc. Reproduction Prohibited 11

12. Quiz
What percentage of enterprise data do firms
use for analytics?
A. 12%
B. 34%
C. 53%
D. 76%
Enterprise
Data
Source: Forrester Research
© 2013 Forrester Research, Inc. Reproduction Prohibited 12

13. #BigData

14. Trend
Big Data means all your data.

15. Most technology decision makers get it; 30% of
business decision makers are confused.
30%
7%
12%
21%
30%
9%
8%
14%
35%
34%
The term “big data” is very
confusing; not sure what it
means
It’s a bunch of hype with little
substance and few new ideas
It’s about new technologies
that allow us to handle more
data
It’s an extension of existing
analytics and BI practices
suited for data that is larger
or faster than we are used to
It’s a whole new way of
thinking about the value in
data that requires new
analytics and leverages
some new technologies
Business Decision Makers Technology Decision Makers
Base: 452 North American technology decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
Base: 249 North American business decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
© 2013 Forrester Research, Inc. Reproduction Prohibited 15

16. Big Data gushes from many sources…
• Data described by a schema
• Relational database, XML, delimited flat file,
system events
Structured
text
• Free-form text
• Email, documents, tweets, blog comments,
Facebook status, genome
Unstructured
text
• Audio, images, video
• Surveillance cameras, geological survey maps,
Siri voice
Binary
© 2013 Forrester Research, Inc. Reproduction Prohibited 16

17. …but, most firms take comfort in traditional
sources.
“How important are the following data types to your firm's overall business strategy?”
Answers 4 and 5 on a scale where 1- not at all important and 5 – very important
31%
28%
4 5. very important
21%
18%
31%
29%
23%
18%
14%
15%
13%
14%
10%
18%
28%
37%
27%
5%
10%
7%
8%
7%
15%
17%
12%
8%
11%
22%
22%
44%
41%
36%
26%
53%
Planning, budgeting, forecasting data
Transactional data from corporate packaged apps
Customer data
Transactional data from corporate custom build apps
Home-grown data stored in spreadsheets or other desktop applications
Unstructured internal data
Product data
Log data from corporate systems
Scientific data
Third party data sets
Partner data
Video, imagery & audio
Sensor data other than mobile devices
Weblog data from publically facing sites
Consumer mobile device data
Social network data
Unstructured external data
Base: 634 Business Intelligence users and planners
Source: Forrsights BI/Big Data Survey, Q3 2012
Still lots of opportunity.
New opportunity?

18. eCommerce
MRP
Web analytics
eCommerce
Web
Mobile
Finance
Customer Service
CRM
Claims
BPM
Excel & Access
Data warehouse
Planning
Email
Customer Service
ERP
Marketing
Social Media
POS
Field Operations
VOC
Workforce/HR

19. 110010011011001
010010011011001
010011001101101
010010011011001
Historical
Transactions
Customer data
Ops

20. 20

21. Data
Gather all your data and do it cost effectively.

22. Process
Now, analyze the heck out of it - every which way.

23. #IoT

24. Applications are blind – use sensors to make
them see.

25. If you can measure it and it’s connected
to the Internet, then you can use it
© 2013 Forrester Research, Inc. Reproduction Prohibited 25

26. Ubiquitous computing
Ambient intelligence
Everyware
Pervasive computing
Cognitive computing
Smart world
Connected world
Physical computing
Context-aware pervasive systems
Machine-to-machine
Industrial Internet
Internet of everything
Thingternet
Sensor revolution
© 2013 Forrester Research, Inc. Reproduction Prohibited 26

27. #Predictive

28. Trend
Data science finds hidden, new knowledge and
predictive models

29. Predictive analytics means faster decisions
“What is your firm's/business unit's current use of the following technologies?”
13%
10%
24%
21%
20%
18%
20%
16%
21%
33%
29%
37%
57%
54%
50%
49%
58%
56%
81%
15%
21%
27%
32%
19%
33%
42%
35%
50%
59%
77%
Reporting
Dashboard
Web Analytics
Performance analytics
Embedded Analytics
Olap
Process Analytics
Location Analytics
Search/Interactive Discovery
Predictive Analytics
Metadata Generated Analytics
Text Analytics
Advanced Visualization
Streaming Analytics
Non Modeled Data Exploration And Discovery
2014
2012
Source: Forrester Research
+52%

30. Predictive models can be very powerful
and profitable, but understand that:
› Predictive models are about probabilities, not
absolutes
› Predictive models may not exist for every
question
But, when they work they give your firm an “unfair”
advantage.
© 2013 Forrester Research, Inc. Reproduction Prohibited 30

31. Data scientists use a
combination of statistical
and machine learning
algorithms to find
patterns and predictive
models.
© 2013 Forrester Research, Inc. Reproduction Prohibited 31

32. Data science is very different from traditional
analytics
Traditional Analytics Predictive Analytics
• Choose a business outcome to improve
• Discuss and decide what data will be relevant
• Develop a data model
• Design reports and dashboards
• Choose business outcome to improve
• Assemble all possible data
• Run algorithms to find relevant data & predictive
model
• Use the predictive model
© 2013 Forrester Research, Inc. Reproduction Prohibited 32

33. Recommend
How can you provide a perfect , individualized
product recommendation?

34. Turkey
How can you predict where customers will be
on Thanksgiving.

35. Activity
How can Spotify use accelerometer data
generated by customers while they listen?

36. #Streaming

37. Trend
Streaming data is flowing by, and value
is slipping away.

38. Streaming analytics means real-time business
“What is your firm's/business unit's current use of the following technologies?”
13%
10%
24%
21%
20%
18%
20%
16%
21%
33%
29%
37%
57%
54%
50%
49%
58%
56%
81%
15%
21%
27%
32%
19%
33%
42%
35%
50%
59%
77%
Reporting
Dashboard
Web Analytics
Performance analytics
Embedded Analytics
Olap
Process Analytics
Location Analytics
Search/Interactive Discovery
Predictive Analytics
Metadata Generated Analytics
Text Analytics
Advanced Visualization
Streaming Analytics
Non Modeled Data Exploration And Discovery
2014
2012
Source: Forrester Research
+62%

39. Big data isn’t just about lakes...

40. . . . it’s also about streams and raging
torrents of information.

41. Successful streaming analytics programs
bring disparate data sources together.

42. Analyzing data as streams and lakes
Lakes Streams
› Ingested and stored in a data
warehouse
› Multiple sources of data
› Analytics run weekly, daily, or
hourly
› Insights used to modify future
actions
› Does collect data in realtime
› Multiple sources of data
› Immediately fed to streaming application
› Analytics run continuously, second and
subsecond responses
› Insights used to proactively adjust
immediate and future actions
© 2013 Forrester Research, Inc. Reproduction Prohibited 42

43. How can you warn other drivers that the
road is slippery to avoid a crash?

44. #Wrangling

45. Trend
Data science exacerbates traditional data
management challenges.

46. Data prep is the most time consuming task.
Identify data that is relevant to
the business goal.
Integrate and enrich the
data into an analytical
data set
Run statistical and machine
learning algorithms to find
the model
Test the model to make sure it
will work
Measure the effectiveness
of the model in the real-world
Use the model in
applications

47. Data science exacerbates traditional data
management challenges
• Advanced analytics does not operate on
Complete preconceived notions of what data is valuable
Accurate • The quality of the data must represent reality
• Relationships between disparate data sources
Linked must be established
• Some data must be enriched with external or real-Enriched
time streaming sources
• Insights and models must be updated as new data
Continuous is generated
© 2013 Forrester Research, Inc. Reproduction Prohibited 47

48. #Apps

49. Predictive apps anticipate a customer’s intent
and adapts to serve them.
Trend

50. © 2013 Forrester Research, Inc. Reproduction Prohibited 50

51. Trip
1
Easy. Buy a copper tube ice maker kit.

52. Trip
2
Buy a shut-off valve for the copper
tubing.

53. Trip
3
Buy a T-connector to tap the cold water
supply line.

54. Trip
4
Whoops. Also need to buy a hacksaw to
cut the copper pipe.

55. Trip
5
Finally. A special drill bit to make a hole
in the kitchen floor for the copper
tubing.

56. Predictive apps can make your
customers feel intensely loyal.

57. #Opportunity?

58. Trend
The velocity of business requires
pervasive analytics.

59. Find opportunities for pervasive
analytics
› Walk through critical or challenging business processes
• At each step of the business process ask how analytics could
improve the process
› Walk through customer journey to improve customer
experience
• At each step of the customer journey, ask how analytics could
improve the customer experience
© 2013 Forrester Research, Inc. Reproduction Prohibited 59

60. “Knowledge is
power profit.”
Francis Bacon (1561–1626)
Founder of the modern scientific
method to establish causation
between phenomenon.

61. #Imagination

62. What kinds of
analytics could your
business use if it had
a pervasive analytics
platform?

63. Thank you
Mike Gualtieri
mgualtieri@forrester.com

64. Analytics
Everywhere
Winning the Data Race with Pervasive
Analytics
Clarke Patterson// Sr Director Product Marketing

65. Data silos

66. Data silos
Limited frameworks

67. Data silos
Limited frameworks
Fragmented admin
& security

68. 68
Acting on data is a clunky process
A marketing
analyst sees a
campaign isn’t
performing.
1

69. 69
Acting on data is a clunky process
1
2
She wants to better
understand the cross
channel campaign by
correlating data from sales,
marketing, web, and social
data. She makes a data
request to IT.

70. 70
Acting on data is a clunky process
1
2 3
The IT request stalls and
requires custom
development that will take 3
months to set up.

71. 71
Acting on data is a clunky process
2 3
1 4
In the mean time she
continues with her limited
data and makes gut
decisions.

72. 72
Acting on data is a clunky process
2 3
1 4
She guesses wrong and 5
doesn't hit her campaign
goals.
X

73. 73
Cloudera’s
enterprise
data hub
Unified
data
Unified
security &
administration
Unified
framework

74. 74
Pervasive
analytics
Innovate
Extend Empower

75. 75
Imagine if this could be different
1
A marketing analyst
can monitor her
campaign in near real
time.

76. 76
Imagine if this could be different
1 2
She can view multiple
data sources from
one view and
receives alerts when
goals aren't met.

77. 77
Imagine if this could be different
1 2 3
In the alerts she receives
recommendations based
on historic campaigns, and
the current campaign
environment, on the best
tactical actions to course
correct the campaign.

78. 78
Imagine if this could be different
1 2 3 4
She incorporates the
recommended
tactics into her
campaign.

79. 79
Imagine if this could be different
1 2 3 4 5
She pulls a report
and hits her goal.

80. 80
Preparing for Pervasive Analytics
Data Sources Data Analysis Data Serving
Human Data
Discovery
Structured
Unstructured
Machine
Response
Single Analysis
Data
Applications
Data Processing &
Storage
Batch
Stream
Extend
Innovate
Empower
Store

81. 81
Preparing for Pervasive Analytics
Data Sources Data Analysis Data Serving
Structured
Unstructured
Machine
Response
Single Analysis
Data
Applications
Data Processing &
Storage
Batch
Stream
Extend
Innovate
Empower
Human Data
Discovery
Store

82. 82
Preparing for Pervasive Analytics
Data Sources Data Analysis Data Serving
Structured
Unstructured
Machine
Response
Single Analysis
Single Analysis
Data
Applications
Data Processing &
Storage
Batch
Stream
Extend
Innovate
Empower
Human Data
Discovery
Machine
Response
Data Applications
Store

83. 83
The Iterative Process of Analytics
Data
Generation
Batch Processing
Data Discovery
Analysis
Technique
Batch Processing
Report, Model,
or Rules
Analyst
Discovery
Flow

84. 84
The Iterative Process of Analytics
Data
Generation
Batch Processing
Data Discovery
Analysis
Technique
Batch Processing
Report, Model,
or Rules
Analyst
Discovery
Flow
Data
Generation
Stream or Batch
Processing
Respond to Data
Feed Data
Application
Optimize Report,
Model, or Rules
Operational
Analytics
Flow

85. 85
Yesterday – Limited
structured data storage
Today – Unlimited
structured and
unstructured storage

86. 86
Yesterday – Scattered,
limited processing and
analytical frameworks
Today – Unified,
diverse frameworks

87. 87
Yesterday – Segmented
management and
security
Today – Unified data/
system security and
management

88. An energy analytics
provider, Opower has
saved consumers
$500M to date

89. Extend:
Hbase storage and
batch processing
Innovate:
BI tools and ad-hoc
SQL
Empower:
Hbase serving and
analytic roll up reports

90. 90
Fire Bronze Salt Gold Oil

91. Lead the data rush

92. Thank you.