Presentation slides of: It’s Not About Big Data – It’s About Big Insights - SAP Webinar - 20 Aug 2013 - PDF Scott Mackenzie - Sr. Director, Platform & Analytics CoE Michael Golzc - CIO for SAP Americas Ken Demma - VP, Insight Driven Marketing 20 Aug 2013 - Webcast - http://goo.gl/T74WAL

1. Getting Big Value from Big Data
August 20, 2013 - Webinar

2. © 2013 SAP AG. All rights reserved. 1
Agenda
1. Big Data “Art of the Possible”
2. Insight Driven Marketing
3. CIO View: How SAP Uses Big Data
4. SAP Solutions & Services
Scott Mackenzie
Sr. Director, Platform & Analytics CoE
Michael Golz
CIO for SAP Americas
Ken Demma
VP, Insight Driven Marketing

3. © 2013 SAP AG. All rights reserved. 2
Lots of Hype and Expectations
A Reality Check
I know Big Data’s
Important, I just don’t
know where to get
started.
We’ve got a pilot,
we’re trying to figure
out where to go next.
Big Data? We’re not
leveraging the data
we already have!
We have a strategy,
but we’re trying to
figure out how to
implement it.
It’s not about Big
Data, it’s about
Big Insights!
This isn’t a nice to
have, it’s a must have
initiative to survive!

4. © 2013 SAP AG. All rights reserved. 3
Big Data is Among Us
Terabytes  Petabytes  Zettabytes
**IDC Digital Universe Study Extracting Value from Chaos;
http://www.dbms2.com/2008/10/15/teradatas-petabyte-power-players/
500+
EACH DAY
TERABYTES
LARGE NORTH AMERICAN
FINANCIAL SERVICES FIRMS
1.5+PETABYTES
1.8
IN 2011, THE AMOUNT
OF DATA SURPASSED
ZETTABYTES

5. User adoption is low
75% of Enterprise
Employees will need
analytics by 2020…
yet only 10% use
today.
How will you
drive analytic
use?
10%
75%
Use Analytics
Today
Need Analytics
by 2020
$2.01B
Annual revenue increase
possibility if the median
Fortune 1,000 business
increased the usability of
its data by just 10%
1,000%
return on investment for
every $1 spent on analytics
Nucleus Research, Gartner, Fortune Magazine

6. New information signals
:-)
Brand
Sentiment
Higher NPS
360O Customer View
Loyal Customers
Product
Recommendation
More Sales
Propensity to
Churn
Greater
Retention
Real-time Demand/
Supply Forecast
More Efficient
Predictive
Maintenance
Less Downtime
Fraud Detection
Lower Risk
Network
Optimization
Lower Cost
Insider Threats
Greater
Security
Risk Mitigation, Real-
time
Retain Market Value
Asset Tracking
Increase Productivity
Personalized Care
Loyal Customers
What signals are
you missing?
“
”
In 2011 the amount
of data surpassed
1.8 Zettabytes
90% of the data in
the world today has
been created in the
last two years
alone
IDC Digital Universe
Study Extracting
Value from Chaos

7. A changing relationship with
information
From mass
production to
mass
specialization
Personalized
Insights
Advanced Planning
and Forecasting
Sensing and
Responding
Predictive
Modeling
Real-time Reporting
and Analysis
“
”
Every product and
service will be
offered to us in
exactly the way we
need it, not how
manufacturers want
to deliver it.
A Demographic of One,
Michael S. Malone

8. Network of Truth
Connecting people
to data
Real-time data
platform
Optimized for people
Information culture
Automate where
possible
“
”
70% of respondents
can envisage a “killer
application” for big data
that would be “very
useful” or “spectacular”
for their business.
The majority chose not
to disclose what that
application would be
because it would
provide a competitive
advantage.
AIIM survey of 345
Information
Professionals 2012
Transaction
Engine
Dimensional
Engine
Analytic
Engine
Predictive
Engine
Text
Engine

9. Information Culture
Use information as a strategic
asset in decisions
Build and tell fact-based
stories
Maximize performance with
effective use of information
Connecting people
to data
“
”
The stone age was
marked by man's
clever use of crude
tools; the
information age, to
date, has been
marked by man's
crude use of clever
tools.
Anon

10. © 2013 SAP AG. All rights reserved. 9
Has your BI Strategy been updated for Big Data?
SAP BI Strategy Framework
Objectives
Business
Needs
Business
Benefit
Technology Organization
Background and
Purpose
Current State and
History
BI Objectives and
Scope
Summary of BI
needs
Envisioned To-Be
State
Priorities and
Alignment
Value Proposition
of BI
Expected Benefits
– Future State KPI
Business Case
Information
Categories
Architecture and
Standards
BI Applications
Governance
Structure
Program
Management
Roadmap and
Milestones
Measurement
Education /
Training
Support
User Engagement and Change Management are
critical success factors. Do you have a BICC?

11. © 2011 SAP AG. All rights reserved. 10
SAP Big Data Analytics Maturity Model
Levels of performance across 5 key best practice domains
Level 1 Level 2 Level 3 Level 4
People &
Skills
Use Cases
Governance
No specific skills,
Executive Audience,
Personal Service
Some limited skills to
bring data into decision
making
BI Roles, Stakeholders
and regular information
skills
Big Data Culture,
Information integration in all
practices, protecting info
assets
No Big Data business
programs, seen as
technology
Line of Business example
use cases; coping.
Understanding and
managing Big Data
insights
Big Data Business Model
Innovation
No Big Data Governance Business Driven Big Data
Governance
Competency Center & Big
Data Governance
Enterprise-wide Big Data
Governance with Business
Leadership
Standards &
Practices
Do not exist or are not
uniform
Evolving effort to
formalize
Exist but are not uniform Uniform, followed and
audited
Information &
Application
Architecture
No Big Data in any
Process
Some Isolated Big Data
Applications
Big Data Projects across
business
Big Data Drives Business
Design

12. © 2013 SAP AG. All rights reserved. 11
Best Practices Implementation Approach
for Big Data Analytics
Step 1: Assess where you are today
Step 2: Define where you want to go
 What are the top 3-5 business objectives?
 What key use cases are needed?
 What analytics are critical? What data do you need/have?
Step 3: Identify the gaps
Step 4: Develop a roadmap to get there
Step 5: Build consensus

13. © 2013 SAP AG. All rights reserved. 12
Agenda
1. Big Data “Art of the Possible”
2. Insight Driven Marketing
3. CIO View: How SAP Uses Big Data
4. SAP Solutions & Services

14. © 2013 SAP AG. All rights reserved. 13
What BIG DATA Means at SAP Marketing…
1.0B
50M
800/200
4.0M…2.0M
2.0B
5 0 0 M
27M-25M

15. © 2013 SAP AG. All rights reserved. 14
What BIG DATA Means at SAP Marketing…
Large volumes of transactions processed
Large data sets used for analysis and
insight development
Combining of data sources…
• Customer Master Data
• Derived and predictive data
• Web data
• Social data
• Unstructured data
• Community data
Unconnected systems combined…
intelligence appended

16. © 2013 SAP AG. All rights reserved. 15
What BIG DATA Means to SAP Marketing…
Think it…Deliver it
Velocity of insights and outputs
Quality of Marketing Science
Focus on user-consumption and user-
direction
New areas of analysis…
…More analysis in current areas
Unleash creativity

17. © 2013 SAP AG. All rights reserved. 16
BIG DATA means Insight-Driven Marketing
Marketing
Optimization
Personalized Lead Delivery
to sales agents
World-wide Demand
Management & Optimization
CMO Dashboard
Insight-Driven
Events
Product
Recommendations
Digital Experience
Personalization,
Optimization & Insight
Social and Voice of
the Customer Insight Always on Marketing
Effectiveness

18. © 2013 SAP AG. All rights reserved. 17
In short…BIG DATA is affording more & better Marketing Science
Increasing data volumes while
concurrently reducing the technical
barriers of data sourcing,
integration, processing power,
preparation and delivery…
Allow for ubiquitous Marketing
analytics, delivered more readily,
more consumable and with more
impact
Increased Technical Abilities Greater Human Outcomes

19. © 2013 SAP AG. All rights reserved. 18
Agenda
1. Big Data “Art of the Possible”
2. Insight Driven Marketing
3. CIO View: How SAP Uses Big Data
4. SAP Solutions & Services

20. © 2013 SAP AG. All rights reserved. 19
Determining your ‘Big Data’ needs
VisualizePredictAnalyze Report
You need Big Data solutions if your
current IT systems limit your ability to:
Capture Engage

21. © 2013 SAP AG. All rights reserved. 20
Understanding the IT Environments that need to support
Big Data
Information Views
EDW / Data Marts
Data Mining /
Predictive Analysis
Real-time
Database
Insight
Discovery Real-time Value
Business
Applications & Processes
Analytic Tools, Custom Data
Analysis Applications
BI Tools
Business
Intelligence
Analytic Data Warehouse
Transactional
Databases
Other Application/
Data Sources
Social Media
Content
Unstructured
Content
Machine
Data
00110101
10010110
01001101

22. © 2013 SAP AG. All rights reserved. 21
Technology Innovation: In-memory Computing
Yesterday Today
Disk
Partitioning
Insert Only on Delta Compression
Row and Column Store
No aggregatesMemory
+
+
+ +
Memory
Logging and Backup –
Solid State / Flash / HDD
CPU
Multi-Core
Massively Parallel
SingleOptimized Platform
64-bit address space
supports 2TB RAM
100GB/s throughput
Software and data reside on HDD
• IO constraint
• Support many platforms
• Optimized for None
• Take advantage of latest advances in hardware
• Minimum IO time
• Optimized for x86 platform
Disk
CPU
+

23. © 2013 SAP AG. All rights reserved. 22
SAP HANA Transforms both Businesses and IT
Sharpen marketing effectiveness
56x faster reporting: micro-targeted
customer offers
Accelerate monthly close & spending insight
75% reduction in CRM query
~23 to 6 seconds
Launch new products or markets
400x faster report execution: Forecast
sales-trends in real-time
Remote roadside diagnostics in real-time
Analyze 15 years 1 TB data
in seconds
Deeper customer relationships
360 customer view and comprehensive
experience
Reduce waste & fraud in government fund
<2 min for detecting 100,000 names over
90M records
Identify cancer DNA variants for treatment
216x faster results: 3 days  20 minutes
Improve diagnostic through pattern detection
300M records; analysis in 2-10 seconds
Predict customer purchase sentiment
Seasonality Analysis in 5 seconds
Improve labor utilization
1131x faster reporting time
“Perfect order” experience
60x faster real-time insights

24. © 2013 SAP AG. All rights reserved. 23
Big Data – Big Insights in Healthcare
SAP HANA powers the
“Oncolyzer”, which can
help doctors find the best
therapies for 15 million
of new cancer patients
each year.

25. © 2013 SAP AG. All rights reserved. 24
SAP powers analytics that
track more than 6 billion
U.S. stock trades per day to
identify fraud and protect
investors.
Big Data – Big Insights in Financial Services

26. © 2013 SAP AG. All rights reserved. 25
SAP Runs SAP
Our SAP HANA Journey
• Sales Pipeline (CRM)
• Profitability Analysis (CO-PA)
• Asset Accounting (FI-AA)
• Overhead Management & CostCenter-Analysis
• Rapid Deployment Solutions (e.g. FIN RDS)
• SAP Community Network – Sentiment Analysis
• Business Warehouse (BW) on HANA
• Business Planning & Consolidation integrated
to BW-Integrated Planning
• Cash & Liquidity Management
• Energy Management
Business
Suite on HANA
Side-by-Side
Primary Data
Store for BW
New
Applications
CRM on HANA LIVE
ERP on HANA in August

27. © 2013 SAP AG. All rights reserved. 26
SAP Runs SAP HANA – Example
Lead-2-Revenue Automation
One Global Platform Supporting Marketing While Connecting with Sales
OnDemand On-Premise
HANA
More Sales
Ready Leads
Faster At a
Fraction Of The
Cost
Increase In
Revenue
Expand Funnel
Accelerate
Funnel
Conversion
Rate

28. © 2013 SAP AG. All rights reserved. 27
Agenda
1. Big Data “Art of the Possible”
2. Insight Driven Marketing
3. CIO View: How SAP Uses Big Data
4. SAP Solutions & Services

29. © 2013 SAP AG. All rights reserved. 28
SAP Real-Time Data Platform
Unified open software platform for real-time business
SAP Real-Time Data Platform foundations
● Cross-paradigm data access for new
models of value discovery.
● Hyper-performance on all classes of
application and usage scenarios
● Price-Performance value across all use
cases
Benefits
● Execute, record, analyze, and optimize
without system limitations
● Embrace and extend across variations of
data forms and processing models
● Common modeling, integrated
development environment, shared
systems management infrastructure, and
deployment-independent solutions
● Trusted and unified data environment
In-memory/real-time
SAP HANA
SAP Real-time Data Platform
SAP Sybase ESP
streams
SAP Sybase SQL
Anywhere
mobile & embedded
SAP Sybase IQ
EDW
SAP Sybase ASE
transactions
SAP Data Services
Information management*
Common programming APIs
SAPSybasePowerDesigner
modeling
SAPSybaseControlCenter
monitoringHadoop
Big Data
* Information management solutions include: SAP Data Services Enterprise, SAP Enterprise Master Data Management,
SAP NetWeaver Information Lifecycle Management, SAP Enterprise ECM solutions by OpenText, SAP Sybase Replication Server

30. SAP HANA Insights: Big Data Starter Package
*SAP BusinessObjects business intelligence (BI) solutions; SAP solutions for enterprise information Management (EIM);
Built by Sanjay Poonen, Copyright SAP, Representative figures based off CIO interviews, showing approximate proportional quantities of IT spending in Analytics
TCO Reduction
by Approx 60%
Traditional Stack = $15
SAP HANA Insights = $6
Oracle DB
(e.g. Exadata)
Informatica ETL
BusinessObjects BI*
SAS Predictive
DBA and
IT Costs
Teradata/Exalytics
$4
$1
$3
$1
$4
$2
$4
$2DBA and IT Costs
BI Suite
HANA Enterprise
Predictive
SAP HANA Insights

31. SAP BI Analytics Edition Package
SAP Business Objects
BI Suite
Sybase IQ
(32 cores / instance)
Data Integrator
(10 CPU)
+
+
Up to €2.4 Million in Savings
BI Suite
(Full Use)
Sybase IQ Enterprise
(32 Cores / instance – RUNTIME)
Data Integrator
(10 CPU / instance – RUNTIME)
SAP BI Analytics Edition

32. © 2013 SAP AG. All rights reserved. 31
How SAP Can Help
Vision
• Vision Workshop
• Innovation Day
• Co-Innovation
Operationalize
• Design Thinking Use
Case Workshop
• BI Strategy
Assessment/ Update
• Big Data/Business
Analytic Services
Pilot
• Full Day Big Data
Workshop
• Pilot Planning &
Roadmap
• SAP Analytics Insights
(Big Data Starter Kit)
Education – Technologies – Services – Industry Expertise

33. © 2013 SAP AG. All rights reserved. 32
Questions?
To Learn More
Call: 1 888-817-2292
Visit: www.sap.com/bigdata

34. Thank You!

35. © 2013 SAP AG. All rights reserved. 34
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