The document discusses the digital transformation era, highlighting Moore's Law and its implications for computing power and the data-driven economy. It emphasizes the need for businesses to adapt to massive data growth and leverage real-time insights to improve productivity and redefine business models. The text advocates for in-memory computing technologies, like SAP HANA, to facilitate this transformation across various industries.

1. The Computing Age
The
Digital Transformation
By Didier Mamma
Vice President of Big Data | IoT EMEA

2. What have been the most important development in human history?
Source Second Machine Age Erik Brynjolfsson and Andrew McAfee,Made by Didier Mamma Vice President of Big Data | IoT EMEA

3. What have been the most important development in human history?
Source Second Machine Age Erik Brynjolfsson and Andrew McAfee,Made by Didier Mamma Vice President of Big Data | IoT EMEA

4. © 2011 SAP AG. All rights reserved. 4
Moore’s
Law
Made by Didier Mamma Vice President of Big Data | IoT EMEA

5. Power doubling
Costs
Moore’s Law Effects
Made by Didier Mamma Vice President of Big Data | IoT EMEA

6. Source Second Machine Age Erik Brynjolfsson and Andrew McAfee,
Power doubling
Costs
Source Second Machine Age. Erik Brynjolfsson and Andrew McAfee,
The spread of Moore’s Law
Made by Didier Mamma Vice President of Big Data | IoT EMEA

7. Moore’s Law Effects
1,8Teraflop/s+ 2 Camera & Photo
+ Gyroscope,
+Accelerometer, wifi, bt,
+ Micro, Built-in keyboard
+ GPS, touch screen
+ light, sensors & mobile…
Digitize Everything Digitize Network Digitize Output
Made by Didier Mamma Vice President of Big Data | IoT EMEA

8. © 2012 SAP AG. All rights reserved. 8Confidential
Computing
Age
Made by Didier Mamma Vice President of Big Data | IoT EMEA

9. From DARPA Grand Challenge
2004 DARPA's debacle in the Desert
Behind the scenes at the DARPA Grand Challenge,
the 142-mile robot race that died at mile
Moore’s Law Effects
Made by Didier Mamma Vice President of Big Data | IoT EMEA

10. Moore’s Law Effects
To the triumph of Project
Chauffeur in 2012
Less than a decade to reach the holy graal
Made by Didier Mamma Vice President of Big Data | IoT EMEA

11. The New Division of Labor
How Computers Are Creating the Next Job Market
Frank Levy & Richard J. Murnane
“Computer are good at following rules… but loosy for
pattern recognition and complex communication….”
Moore’s Law Effects
Made by Didier Mamma Vice President of Big Data | IoT EMEA

12. KirabyAmazon Baxter Googlecar
Revolution in robotics, logistics & automation
RoboticChef
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13. © 2012 SAP AG. All rights reserved. 13Confidential
The Inflection
Point is Now
Made by Didier Mamma Vice President of Big Data | IoT EMEA

14. © 2012 SAP AG. All rights reserved. 14Confidential
Value Chain Disruption
GE dismantles GE Capital;
plans $90B to investors – NYT 2015
Hewlett-Packard Set to Break Up
75-Year-Old Company – WSJ 2015
PayPal Eclipses eBay’s
Marketplace Ahead of Spin-Off
Time 2015
DISAGGREGATION
Competitive attack on the most profitable or vulnerable step in
the value chain
DISINTERMEDIATION
The elimination of traditional non-valued added intermediaries by
changing who maintains the relationship with the customer.
Volume
Variety
Velocity
Made by Didier Mamma Vice President of Big Data | IoT EMEA

15. ----------------------- DIGITIZATION ---------
Volume
Variety
Velocity
Every Business is Digitally Remastering

16. Every Business is Digitally Remastering
Made by Didier Mamma Vice President of Big Data | IoT EMEA

17. Cloud
Networks
People & Things
Mobility
Made by Didier Mamma Vice President of Big Data | IoT EMEA

18. 2020: Digital universe = 40
Zettabytes
2012: Digital universe = 2 Zettabytes
2014: 31% of enterprises
managing more than 1 Petabyte
1 Zettabyte (ZB) = 1 million Petabytes
(PB); Sources: IDC and IDG Enterprise
85% of growth from
new types of data with
machine-generated
data increasing 15x
Social
Networks
Machine
Generated
Documents,
Emails
OLTP, ERP,
CRM
Geolocation
Data
Sensor
Data
Web Logs,
Click
Streams
Data are growing exponentially
Made by Didier Mamma Vice President of Big Data | IoT EMEA

19. SALESDATA SERVICE DATAENTERPRISE DATA
PROSPECT CONSUMER PROMOTER
SOCIAL DATA SOCIAL DATA
MARKETING DATA Supply chain
INVENTORY BILLING
RETURNS
WINNING EXPERIENCE
SUPPLIER
The Customer 3.0
Made by Didier Mamma Vice President of Big Data | IoT EMEA

20. RELEVANT
CONTENT
WHAT THEY
HAVE DONE
WHAT THEY
MAY DO
WHAT THEY
ARE DOING NOW
REAL-TIME
INDIVIDUALIZATION
RESAGGREGATION
Rethink the vulnerable step of value
chain
REINTERMEDIATION
Create new valuable added
intermediaries by reconnecting
with the customer.
The Customer
3.0
Made by Didier Mamma Vice President of Big Data | IoT EMEA

21. The Current Reality
Organizations Articulate
Digital Transformation as a
Priority but are Not Able to
Execute Today
Massive connectivity is transforming
everything.
Re-Imagine Business Process
driven by data
Fundamental business process
change and/or elimination due to
digitization
Increase dramatically the
output per worker
Massive workforce productivity
improvementsto existing processes
based on real-time information given
to make the right decisions and drive
immediate impact
Business Model
Transformation
Reinvent your business and drive
competitive advantage by expanding
beyond traditional industry boundaries
and transforming from an asset to a
service/outcome-based organization
78%
The Future is
Now
15%
The Current
Reality
Organizations Articulate
Priority
$1.36 Trillion
Of organizations have
identified digital
transformation as a critical
priority to address within the
next two years**
of companies have a
plan to address digital
transformation
Additional Productivity
& GDP Output in 2020
from digitization*

22. © 2012 SAP AG. All rights reserved. 22Confidential
Big Data Value ModelBusinessValue
Level of Intelligence
PROCESS DRIVEN
processes consume DATA
DATA DRIVEN
DATA consume
processes & rules
Descriptive
Descriptive Analytics What
Happened?11
Diagnostic
Diagnostic Analytics Why did it
Happen?22
Predictive
Predictive Analytics What will
Happen?33
Prescriptive
Prescriptive Analytics How can
we make it Happen?44
Realtime
Batch
Made by Didier Mamma Vice President of Big Data | IoT EMEA

23. © 2012 SAP AG. All rights reserved. 23Confidential
Volume
Velocity
Patterns
Responses
I Know
that I know
1
I don’t know
that I don’t
know
2
I know that I
don’t know
3
I don’t know
what I know
4
BigDataValueModel
Made by Didier Mamma Vice President of Big Data | IoT EMEA

24. © 2012 SAP AG. All rights reserved. 24Confidential
Volume
Velocity
Patterns
Responses
I Know
that I know
1
I don’t know
that I don’t
know
2
I know that I
don’t know
3
I don’t know
what I know
4
BigDataValueModel
What data can
we have access
that are not
capturing?
3
What data do
we have?
1
What data
could we
creates?
2
What are the
weak and
hidden
signals?
4
Made by Didier Mamma Vice President of Big Data | IoT EMEA

25. © 2012 SAP AG. All rights reserved. 25Confidential
Big Data Looks Beyond
Sales of two new products
six weeks after market
introduction
A B
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26. © 2012 SAP AG. All rights reserved. 26Confidential
Big Data Looks Beyond
Sales of two new products
six weeks after market
introduction
Repeat purchases
A B
Made by Didier Mamma Vice President of Big Data | IoT EMEA

27. Business Value vs. Efficiency of Investment
High
Low
Process
Batch
Hindsight
Descriptive
Yesterday
Today
Intermediation, Push,
Products, Mass market
Reintermediation, Pull, Service &
Usage & Experience , One segment
PROCESS
PATTERN
Data
Realtime
Foresight
Prescriptive
Paradigm shift
Made by Didier Mamma Vice President of Big Data | IoT EMEA

28. Technology
PlatformArchitecture
Business
Model
Made by Didier Mamma Vice President of Big Data | IoT EMEA

29. The problem with current IT Landscape
Silos, delay and complexity hinders business agility and innovation
ETL &
Staging
Data
Application silos
Multiple data copies
Batch processing
Partial business view
No real-time insights
Limited ability to innovate
Manufacturing
App
Data
Logic
Finance
App
Data
Logic
Sales
App
Data
Logic
Service
App
Data
Logic
Streaming
App
Data
Logic
Predictive
App
Data
Logic
Analytics
App
Logic
Data
Spatial
App
Data
Logic
ETL &
Staging
Data
ETL &
Staging
Data

30. No waiting for
data access and
processing
Speed
Simplicity
Innovation
All
application logic
(OLTP & OLAP)
processed in one
system
All data types
processed in one
system
ONE In-Memory Platform for ALL applications
Manufacturing
App
Finance
App
Sales
App
Service
App
Streaming
App
Predictive
App
Analytics
App
Spatial
App
Data
Logic Logic Logic Logic Logic LogicLogic Logic
The solution is only possible with in-memory data management
Only data in-memory enables all applications to become real-time

31. © 2014 SAP AG. All rights reserved. 31
Rethink
Yesterday
CPU
Memory
Disc
Software and data
reside on HDD
Today
Multi-Core High performanceMassively Parallel
Partitioning
Insert Only
on Delta
Compression
++++
+Row and Column Store
No aggregates
Logging and Backup – Solid State / Flash / HDD
In-Memory Computing – HANA

32. © 2014 SAP AG. All rights reserved. 32
HANA MORE than just a database a platform
Any Apps
Any App Server
SAP Business Suite and BW
ABAP App Server
Other AppsLocationReal-timeHADOOPMachineUnstructuredTransaction
HANA Platform
SQL, SQLScript, JavaScript
Spatial Text Search
Text
Analysis & Mining
Stored Procedure
& Data Models
Application &
UI Services
Business Function
Library
Predictive Analysis
Library
Database
Services
Series Data
Rules
Engine
Integration & Steaming Services
SAP HANA is the platform for
ALL Applications
A true platform
Converged OLTP + OLAP
Native processing services
Embedded business logic
Supports any application
60% of HANA use cases are outside of the SAP
Landscape
1,600+ start-ups & ISVs developing on HANA
Supports any Device

33. © 2014 SAP AG. All rights reserved. 33
Multi-tenant
Database
Containers
Dynamic
Tiering
Smart Data
Streaming
Graph DB
Services
Smart Data
Integration &
Quality
Hadoop Direct
Access
Series Data
Extended
Application
Services - XS
Predictive
Analytics –
APL, PAL
Application
Function
Modeler - AFM
Text Mining
Text Search &
Analytics
HANA PLATFORM
SAP HANA Platform
OLAP
OLTP
Lowered TCO with
simplified deployment in
Cloud or On-Premise
Enable Internet of
Things & Machine
Control Scenarios
High Performance &
Lowered TCO for Data
Integration
Enterprise Data
Warehousing
Logistics, Social, Telco
etc. scenarios
Big Data Scenarios, multi-temperature
Application Server,
HTML5, JavaScript,
Odata, HTML 5, WServer
Forecasting, Predictive
Maintenance
Semantic Extraction, Classification, Entity&Relationship,
Recognition
Finance, Smart
Metering
Modeling

34. © 2014 SAP AG. All rights reserved. 34
Embracing Hadoop as a Core Technology
In-Memory
Store
Data Processing Engines
SQL Optimizer / Executor
HDFS
YARN
Spark
Vora
Files
Spark
Vora
Files
Spark
Vora
Files
SAP HANA
BENEFITS
• Integration of SAP data
with data lakes
• HANA connectivity on
Hadoop
• Enterprise
Analytics(hierarchies) &
Interactive SQL on
Hadoop data
• Data Tiering from HANA
to Hadoop for OLAP
scenarios using DLM
• Archiving of ERP data
using ILM to Hadoop
Made by Didier Mamma Vice President of Big Data | IoT EMEA

35. DATA is
Everything

36. Economy 4.0
Different challenges with same response
Remote Maintenance and Service
Predictions
Sensors / IoT / M2M
Personalize Medicine
Responsive Manufacturing
Vertical integration
Ultra Fast Fashion
Adaptive Logistics
Made by Didier Mamma Vice President of Big Data | IoT EMEA

37. Economy 4.0
Different challenges with same response
Remote Maintenance and Service
Predictions
Sensors / IoT / M2M
Personalize Medicine
Responsive Manufacturing
Vertical integration
Ultra Fast Fashion
Adaptive Logistics
Intensive Elastic In-Memory ComputingHANA PLATFORM
REVEAL
Infinite Insight / Data science
MONITOR & ACT
Event Stream Processing
VISUALIZE
Lumira
Made by Didier Mamma Vice President of Big Data | IoT EMEA

38. Economy 4.0 Different challenges with same response
Intensive Elastic In-Memory ComputingHANA PLATFORM
REVEAL
Infinite Insight / Data science
MONITOR & ACT
Event Stream Processing
VISUALIZE
Lumira
Manufacturing
App
Finance
App
Sales
App
Service
App
Streaming
App
Predictive
App
Analytics
App
Spatial
App
Microservices Microservices Microservices Microservices Microservices Microservices
NETWORK
CONNECT SECURE MANAGEORCHESTRATE
x,y,z...Appa,b,c..
App

39. © 2012 SAP AG. All rights reserved. 39Confidential
Economy 4.0 scenarios

40. © 2012 SAP AG. All rights reserved. 40Confidential
Route to Innovation
Harvard Business review 2014

41. © 2012 SAP AG. All rights reserved. 41Confidential
THANK
YOU
Made by Didier Mamma Vice President of Big Data | IoT EMEA