Streaming analytics is about knowing and acting on what's happening in your business and with your customers right this second. Forrester calls these perishable insights because they occur at a moment's notice and you must act on them fast. The high velocity, whitewater flow of data from innumerable real-time data sources such as market data, internet of things, mobile, sensors, clickstream, and even transactions remain largely un-navigated by most firms. The opportunity to leverage streaming analytics has never been greater. In this session, Forrester analyst Mike Gualtieri explains the opportunity, use cases, and how to use cloud-based streaming solutions in your application architecture.

1. Using Streaming Analytics To Exploit Perishable Insights
Mike Gualtieri, Principal Analyst
November 2014

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

3. Why?
Meet demand for analytics of all kinds.

4. #Analytics

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

6. Future
History
…but, analytics is alsoabout the future.

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

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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?
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
2%
16%
20%
28%
29%
31%
32%
32%
34%
35%
45%
2%
12%
14%
26%
23%
35%
28%
31%
27%
33%
44%
Other (please specify)
Earlier-generation technology is too expensive
The velocity of data is too high for earlier technologies
The number of data formats that we must be able to…
Analysis requirements change too fast to keep up with
The performance of certain analysis is not sufficient
We don't know what our entire data universe contains,…
We want to access data that was not accessible for us…
Data changes or becomes available much faster than…
Data volumes have grown beyond what we can cost-…
We want deeper insights through advanced analytics
Business decision makers
Technology decision makers
Most want deeper insights through advancedanalytics but familar challenges persist.

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What percentage of enterprise data do firms use for analytics?
A.12%
B.34%
C.53%
D.76%
Enterprise
Data
Quiz

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

11. #Predictive

12. Trend
Data science can find hidden new knowledge and predictive models

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

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›Predictive models are about probabilities, not absolutes
•E.g. 78% chance you will like Breaking Bad
›Predictive models may not exist for every question
•E.g. Economists, elections, etc…
Predictive models can be very powerful and profitable, but understand that:
But, when they work they give your firm an “unfair” advantage.

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Data scientists use a combination of statistical and machine learning algorithms to find patterns and predictive models.

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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

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

18. #BigData

19. Trend
Big Data means all your enterprise data + IoT data

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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
Most technology decision makers get it; 30% of business decision makers are confused.

21. 110010011011001
010010011011001
010011001101101
010010011011001
Historical
Transactions
Customer data
Ops

22. 22

23. Gather all your data to breakdown silos and prepare it for deeper analysis.
Data

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

25. #TooLate

26. Trend
Live data is flowing by, and value is slipping away.

27. Big data isn’t just about lakes…

28. . . . it’s also about raging torrents of data

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›Ingested and stored in a data warehouse
›Multiple sources of data
›Analytics run weekly, daily, or hourly
›Insights used to modify future actions
Analyzing data lakes versus streams
Streams
Lakes
›Does collect data in realtime
›Multiple sources of data
›Immediately fed to streaming application
›Analytics run continuously, second and subsecondresponses
›Insights used to proactively adjust immediateand future actions

30. #Streaming

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

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

33. DEFINITION
FORRESTER
Software that can filter, aggregate, enrich, and analyze a high throughput of data from disparate live data sources to visualize business in real time, detect urgent situations, and automate immediate actions.

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We call these in-the-moment advantages:
#PerishableInsights
Insights that can provide incredible value but the value expires and evaporates once the moment is gone.

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Streaming analytics is only half about ingestion
›High-throughput, uneven ingestion of event, sensor, transactions and just about any periodic data that just flows unrequested
•Architectural concerns such as availability, scalability, and latency (performance) are handled by platform
•Connect to multiple live disparate data sources
35

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The distinguishing magic of streaming analytics is about streaming operators
›Simple and complex analytical operators
•Detect, filter, and/or aggregate events
•Lightweight transformations and enrichment
•Dimensional window operators (e.g. break a geofence, average pressure over 5 minutes)
•Temporal pattern detection (e.g. if A and then B within 2 seconds)
36

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

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The constructs of streaming applications are different from conventional applications…
Filtering
Aggregation/correlation
Enrichment
Location/motion
Time windows
Temporal patterns
Familiar
Unfamiliar

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Data Warehouse
Analytics
Historical
…and, so is the application architecture
Push notifications
Email alerts
HTML5
Dashboards/
visualizations
APIs
Streaming
Analytics Application Platform
Stream 2
Backend Database
Traditional App
API calls/responses
Stream 1
Stream 3

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Streaming analytics platforms enable a whole new class of applications
›Detect , adapt, and act applications require high- performance data access on the front-end and the back- end.
›Provide development tools to create streaming applications
›Reduce development time by simplifying the architectural concerns of performance, scalability, and availability.

41. #IoT

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

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If you can measure it and it’s connected to the Internet, then you can use it

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Ubiquitous computing
Everyware
Ambient intelligence
Smart world
Connected world
Cognitive computing
Pervasive computing
Physical computing
Context-aware pervasive systems
Machine-to-machine
Industrial Internet
Internet of everything
Thingternet
Sensor revolution

45. #Cloud

46. The cloud is perfect for streaming analytics.
Trend

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Lots of streaming data is cloud born
›Mobile, web and IoTdata
›Elasticity of architecture can handling the spikeynessof both ingestion and streaming operator compute
›Lower-latency integration with other services to enrich streams from database, data warehouses

48. #Challenges

49. Garbage In = Garbage Out

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Thinking in streams requires new technology and mindset
›Data silos hinder visibility and prevent streaming insights.
›Big Data strains the ability of legacy technology to delivery handle large, uneven flows of data
›Predictive and streaming analytics capabilities are lacking or non-existent
›There’s a lack of external and contextual data sources that enrich data.
›Developers still think in request/response

51. #StreamingApps

52. Streaming apps anticipate a customer’s intent and adapts to serve them.
Trend

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Streaming analytics can uniquely enable three new tiers of app functionality
Source: April 22, 2014, “Use Sensors To Take Apps To The Next Level Of Customer Engagement” Forrester report

54. Stop
What if you knew your customer was near your store on a sunny day?

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NFL
Sensors in every players’ shoulder pads will change the way we analyze and watch the game

56. How can sensors in police-issued firearms improve safety and response?

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

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

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

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

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

63. Streaming apps can make your customers feel intensely loyal.

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Design principles for customer –facing streaming apps
›Learning who the customer really is
›Detect the customer’s intent in-the-moment
›Adapt functionality and content to match intent
›Optimize for the device (human-computer interface)

65. #Opportunity

66. Trend
The velocity of business requires streaming analytics.

67. #Imagination

68. What kinds of apps could youdevelop if could predict, detect and adapt to what is happening in your business in-the- moment?

69. Thank you
Mike Gualtieri
mgualtieri@forrester.com