Business success relies heavily on taking the right action, at the right time, all the time. And actions are dictated by data. But the batch-oriented, collect-store-contemplate model employed by Big Data Analytics technologies is incomplete because it does not make use of live data in real time. Without live, real-time data insights gathered are not up-to-date, and cannot accurately inform applications and services that would benefit from continuous, real-time context for time-sensitive decisions. To thrive, businesses need to be able to use both live and historical data in their applications and services, continuously, concurrently, and correctly and the only technology currently capable of handling it is streaming analytics. Streaming analytics computes data right now, when it can be analyzed and put to good use to make applications of all kinds contextual and smarter. This webinar held in collaboration with Forrester, Inc., showcased how streaming analytics applications can be built in minutes, to: - Aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any format to identify patterns, detect opportunities, automate actions, and dynamically adapt - Easily ingest streaming data from multiple disparate sources to multiple sources, within and between cloud and on-premises environments - Analyze and act on data as it arrives, without needing to store, eliminating unnecessary security risks and storage costs - Enable real-time analytics with existing business intelligence and data assets.

1. TWEET: during and after the webinar, please use #StreamingAnalytics for live discussions
DIRECT QUESTIONS: please use the box to the right of your screen
RECORDINGS: an edited version of the webinar recording will be emailed after the event
Real time for the bottom line webinar series
EPISODE I: How to stop wasting money on unactionable analytics

2. Perishable Insights – Stop Wasting Money
On Unactionable Insights
Mike Gualtieri, Principal Analyst
Twitter: @mgualtieri

3. #Priority

4. © 2015 Forrester Research, Inc. Reproduction Prohibited 4
52%
53%
53%
54%
58%
64%
64%
65%
66%
73%
75%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Better leverage big data and analytics in business decision-making
Create a comprehensive strategy for addressing digital technologies like mobile,
social & smart products
Create a comprehensive digital marketing strategy
Better comply with regulations and requirements
Improve differentiation in the market
Increase influence and brand reach in the market
Address rising customer expectations
Improve our ability to innovate
Reduce costs
Improve our products /services
Improve the experience of our customers
Customer experience and product innovation
are top priorities.
› Base: 3,005 global data and analytics decision-makers
› Source: Global Business Technographics Data And Analytics Online Survey, 2015

5. For you For all For segments For you
Demographic
Relationships
Hyper-Personal,
Real-Time
Relationships
Personal
Relationships
Mass
Relationships
CustomerExperience
1800 1900 1950 2000 2015

6. Customers want and increasingly expect
to be treated like celebrities.

7. • Learn individual customer
characteristics and
behaviors
• Detect customer needs and
desires in real-time
• Adapt applications to serve
an individual customer
Customer experiences must:

8. #IoT

9. © 2015 Forrester Research, Inc. Reproduction Prohibited 9
82% of enterprises are interested in IoT

10. • Learn individual device and
systems of devices
characteristics and
behaviors
• Detect context in real-time
• Adapt applications to
improve the applications
IoT applications must:

11. Devices have sensors and may have
controllers…

12. …but, IoT applications are not smart
without a brain.

13. #Data

14. Using your best estimate, what is the size of
all data stored within your company?
Source: Forrester Research, September 2015
Base: 100 US Managers and above currently using Hadoop for processing and analyzing data.
Enterprises have plenty of data from both internal and
external sources
10-49
Terabytes
5% 50-99
Terabytes
12%
100-500
Terabytes
54%
Greater than
500
Terabytes
29%
Internal
business
data
49%
External
source data
51%
What % of the data available is from internal
business applications (ERP and business
applications) versus external sources
(social, IoT)?

15. Data is like a drop of rain

16. It forms instantaneously in a cloud

17. And travels far before it ripples

18. #Real-time

19. All data originates in real-time!

21. But, analytics to gain insights is usually
done much, much later.

22. 22© 2016 Forrester Research, Inc. Reproduction Prohibited
“As you look to improve your data processing and analytics capabilities, what aspect of
the implementation is most important to your business? Please select one.”
11%
11%
12%
16%
24%
25%
Quick turnaround on customer requests
More data availability
Expanded access to more business users (i.e., self-service)
Low cost
Advanced analytics capabilities (e.g. predictive. prescriptive,
streaming)
Faster performance (time to value)
Faster time to value and advanced analytics
is most important to business
Base: 100 data science and data analytics leaders at enterprises within the US
Source: A commissioned study conducted by Forrester Consulting, April 2016

23. #WhyWait

24. Insights are perishable.

25. Real-time
insights
Operational
insights
Performance
insights
Strategic
insights
Insight: Shopping for
furniture
Action: Recommend
cleaning supplies
Insight: Profit lower than
goal
Action: Optimize price
Insight: Demand forecast
strong
Action: Increase inventory
Insight: Furniture demand
high
Action: Expand product line
TimetoAct
Perishability
Sub-second to
seconds
Seconds to
hours
Days to
weeks
Weeks to
years
Sub-second to
seconds
Seconds to
hours
Hours to
weeks
Weeks to
years
Enterprises must act on a range of perishable
insights to get value from data and analytics

26. Batch analytics operations take too long
BusinessValue
Time To Action
Data
originated
Analytics
performed
Insights
gleaned
Action
taken
Outdated
insights
Impotent or
harmful
actions
PositiveNegative
Decision
made
Poor
decision

27. Compress analytics operations to maximize
the value of data
BusinessValue
Time To Action
PositiveNegative
Maximum
Business
Value

28. © 2015 Forrester Research, Inc. Reproduction Prohibited 28
Real-time means highly perishable

29. How can you know if you should you make an
offer or send a gentle nudge right now?

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

31. Is this customer thinking about moving to a
rival firm right now?

32. Real-time analytics is necessary to detect
and act on real-time perishable insights.

33. #Challenges

34. 34© 2016 Forrester Research, Inc. Reproduction Prohibited
“What are the technological challenges impeding you from processing and analyzing data more
effectively? Select all that apply.”
6%
18%
18%
22%
27%
29%
35%
35%
37%
We have no technical challenges
Lack of analytical tools
Lack of data management tools
Difficulty in creating data models and/or preparing data for analytics
Too many data formats to integrate effectively
Data is difficult to access from multiple sources
Difficulty integrating data from multiple sources
Time it takes to assemble data for analysis
Data volume is too large
Top technological challenges
Base: 100 data science and data analytics leaders at enterprises within the US
Source: A commissioned study conducted by Forrester Consultin, April 2016

35. The data lake approach is insufficient
because it takes too long
Customer
Reference
Data Lake
Operational
Transactional
Analytics tools Insights
Data
Scientists
Business
intelligence

36. #Streaming

37. Streaming analytics can detect and act on
real-time perishable insights.

38. DEFINITION
FORRESTERStreaming analytics filter, aggregate, enrich,
and analyze a high throughput of data from
disparate live data sources to identify patterns,
detect urgent situations, and automate
immediate actions in real-time.

39. © 2015 Forrester Research, Inc. Reproduction Prohibited 39
Source: Forrester Research
Streaming analytics adoption is rightly surging
“What is your firm's/business unit's current use of the following technologies?”
Source: Forrester's Global Business Technographics Data And Analytics Survey, 2015 and 2014
Base: 1805 (2015), 1063 (2014)
19%
19%
24%
31%
34%
22%
22%
35%
31%
43%
53%
54%
50%
50%
69%
39%
42%
42%
42%
42%
43%
43%
46%
48%
52%
54%
55%
56%
57%
69%
Non modeled data exploration and discovery
Search/interactive discovery
Streaming analytics
Metadata generated analytics
OLAP
Advanced visualization
Text analytics
Location analytics
Predictive analytics
Process analytics
Embedded analytics
Web analytics
Dashboards
Performance analytics
Reporting
2015
2014

40. In-memory (RAM) can access data 58,000 times
faster than disk.

41. Modern applications infuse analytics to respond
in real-time and become smarter
Streaming data
Application
interface
App Logic
Applications
Context
Actions
Real-time
Context
Programmed
Logic
Learned
Logic
Machine
learning
Learning
External
Actions
External
Context
From other data
sources of
applications
To other data
sources or
applications

42. How can you prevent this dude from fleecing
you right now?

43. What are movers and shakers saying about
equities that we cover right now?

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

45. How can you show an ad that this household
will find relevant right now?

46. © 2015 Forrester Research, Inc. Reproduction Prohibited 46
Thinking in streams is different…
› Ingest
› Filter
› Transform
› Normalize
› Link
› Enrich
› Correlate
› Location/motion (geofencing)
› Time windows
› Temporal pattern detection (CEP)
› Business logic/rules execution
› Action interfaces
Continuous Ingestion Continuous Analytics

47. How can an online retailer
sell more motorcycle
helmets and optimize
profits?
› Temporal pattern detection
› Time windows
› Business logic/rules
execution
› Action interfaces

48. © 2015 Forrester Research, Inc. Reproduction Prohibited 48
Streaming analytics enables an entirely new real-
time selling model
› Analytic: When has this user
viewed at least three
motorcycle safety products
including at least one helmet?
› Action: Display most profitable
motorcycle helmets.
› Analytic: What is the real-time
daily total sales of motorcycle
helmets?
› Action: If sales trending lower
than usual, then dynamically
lower price.
Temporal Pattern Detection Time Window

49. #Technology

50. Architecture
• Workload scalability
• Ingestion throughput
• Analytical throughput
• Analytical latency
• Fault tolerance
• Operational management
• Deployment options (cloud)
Stream/event handling
• Event sequencing
• Enrichment
• Business logic
Analytical operators
• Transformation
• Aggregation
• Correlation
• Time windows
• Pattern matching
Applications dev.
• Development tools
• Data connectors
• Extensibility
• Dynamic deployment
Evaluate streaming analytics technology based on
these criteria

51. 11001001101
1
0100100
1
010011001
1
010
1
Historical
Transactions
Customerdata
Security
Ability to ingest structured and unstructured
from multiple sources in real-time.

52. Scale to handle any volume & velocity of data.

53. Process and analyze in real-time.

54. Provide fault-tolerance for mission-critical
business and customer applications.

55. Provide tools that make it easy to manage
and monitor the platform.

56. Offer tools to visualize insights from real-time
data.

57. Development environment that leverages
existing skills such as SQL.

58. The Forrester Wave™: Big
Streaming Analytics
Platforms, Q1 2016
Source: Forrester Research
15 vendor solutions for fast
data ingestion, analysis,
and action.
Mng: Let me know if
you want this slide in
here.

59. #Opportunity

60. Enterprises must act on a range of perishable
insights to get value from big data
Real-time
Insights
Strategic
Insights
Operational
Insights
Performance
Insights
TimetoAct
Perishability
Sub-second to
seconds
Seconds to
hours
Days to
weeks
Weeks to
years
Sub-second to
seconds
Seconds to
hours
Hours to
weeks
Weeks to
years

61. Use streaming analytics to create a whole
new class of real-time customer
experiences.

62. “An investment in
real-time knowledge
always pays the best
interest.”
- Benjamin Franklin
United States founding father,
inventor, and timeless thought
leader.

63. forrester.com
Mike Gualtieri
mgualtieri@forrester.com
Twitter: @mgualtieri

64. SQLstream: leading streaming analytics platform
-empowering people, services, and machines to take the next right action, continuously and in real time
ANALYZE
ACQUIRE
ACT

65. Cloud-
SQLstream powers Amazon Kinesis Analytics

66. StreamLab: development environment-
-from raw data to streaming apps in minutes
User selected
suggestion to execute
Immediately see the
live data & results
Build dashboards with
queries running
Auto generates useful
analytic suggestions

67. REAL-TIME FOR THE BOTTOM LINE WEBINAR SERIES
COMING UP | EPISODE 2: Streaming ingest
October 2016
inquiries@sqlstream.com