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

Perishable Insights – Stop Wasting Money

On Unactionable Insights

Mike Gualtieri, Principal Analyst

Twitter: @mgualtieri

#Priority

© 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

For you For all For segments For you

Demographic

Relationships

Hyper-Personal,

Real-Time

Relationships

Personal

RelationshipsMass

Relationships

Cu

sto

me

r E

xp

eri

en

ce

1800 1900 1950 2000 2015

Customers want and increasingly expect

to be treated like celebrities.

• Learn individual customer

characteristics and

behaviors

• Detect customer needs and

desires in real-time

• Adapt applications to serve

an individual customer

Customer experiences must:

#IoT

© 2015 Forrester Research, Inc. Reproduction Prohibited 9

82% of enterprises are interested in IoT

• Learn individual device and

systems of devices

characteristics and

behaviors

• Detect context in real-time

• Adapt applications to

improve the applications

IoT applications must:

Devices have sensors and may have

controllers…

…but, IoT applications are not smart

without a brain.

#Data

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

Terabytes29%

Internal business

data49%

External source data

51%

What % of the data available is from internal business applications (ERP and business

applications) versus external sources (social, IoT)?

Data is like a drop of rain

It forms instantaneously in a cloud

And travels far before it ripples

#Real-time

All data originates in real-time!

But, analytics to gain insights is usually

done much, much later.

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

#WhyWait

Insights are perishable.

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

Tim

e t

o A

ct

Perishability

Sub-second to

secondsSeconds to

hours

Days to

weeksWeeks 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

Batch analytics operations take too long

Bu

sin

ess

Valu

e

Time To Action

Data

originated

Analytics

performed

Insights

gleaned

Action

taken

Outdated

insights

Impotent or

harmful

actions

Po

sitiv

eN

eg

ative

Decision

madePoor

decision

Compress analytics operations to maximize the value of data

Bu

sin

ess

Valu

e

Time To Action

Po

sitiv

eN

eg

ative

Maximum

Business

Value

© 2015 Forrester Research, Inc. Reproduction Prohibited 28

Real-time means highly perishable

How can you know if you should you make an

offer or send a gentle nudge right now?

How can you warn other drivers that the

road is slippery to avoid a crash right now?

Is this customer thinking about moving to a

rival firm right now?

Real-time analytics is necessary to detect

and act on real-time perishable insights.

#Challenges

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

The data lake approach is insufficient because it takes too long

Customer

Reference

Data Lake

Operational

Transactional

Analytics tools Insights

Data

Scientists

Business

intelligence

#Streaming

Streaming analytics can detect and act on

real-time perishable insights.

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.

© 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

In-memory (RAM) can access data 58,000 times

faster than disk.

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

LogicMachine

learning Learning

External

Actions

External

Context

From other data

sources of

applications

To other data

sources or

applications

How can you prevent this dude from fleecing

you right now?

What are movers and shakers saying about

equities that we cover right now?

How can you warn other drivers that the

road is slippery to avoid a crash right now?

How can you show an ad that this household

will find relevant right now?

© 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

How can an online retailer

sell more motorcycle

helmets and optimize

profits?

› Temporal pattern detection

› Time windows

› Business logic/rules

execution

› Action interfaces

© 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

#Technology

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

110010011

01100

1

0100100

11011

00

1

01001100

11011

0

1

0100100

11011

00

1

His

torica

l

Tra

nsactions

Custo

mer

data

Security

Ability to ingest structured and unstructured

from multiple sources in real-time.

Scale to handle any volume & velocity of data.

Process and analyze in real-time.

Provide fault-tolerance for mission-critical

business and customer applications.

Provide tools that make it easy to manage

and monitor the platform.

Offer tools to visualize insights from real-time

data.

Development environment that leverages

existing skills such as SQL.

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.

#Opportunity

Enterprises must act on a range of perishable insights to get value from big data

Real-time

Insights

Strategic

Insights

Operational

Insights

Performance

Insights

Tim

e t

o A

ct

Perishability

Sub-second to

secondsSeconds to

hours

Days to

weeksWeeks to

years

Sub-second to

seconds

Seconds to

hours

Hours to

weeks

Weeks to

years

Use streaming analytics to create a whole

new class of real-time customer

experiences.

“An investment in

real-time knowledge

always pays the best

interest.”

- Benjamin Franklin

United States founding father,

inventor, and timeless thought

leader.

forrester.com

Mike Gualtieri

mgualtieri@forrester.com

Twitter: @mgualtieri

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

ANALYZE

ACQUIRE

ACT

Cloud-SQLstream powers Amazon Kinesis Analytics

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

REAL-TIME FOR THE BOTTOM LINE WEBINAR SERIES

COMING UP | EPISODE 2: Streaming ingest

October 2016

inquiries@sqlstream.com