The future holds many transformational opportunities. Capitalize on the new technology frontier and realize value previously unattainable with SAP HANA. Learn how SAP and AWS are collaborating to empower businesses, developers, startups and even sports fans to take advantage real time computing in the cloud.
SAP and AWS experts will outline:
• How do SAP and AWS align to support your cloud strategy, large or small?
• What is SAP HANA and how does it enable you to run your business in real-time?
• Use cases for developers and enterprise; and capabilities including analytics, business processes, sentiment data processing, and predictive.
• How to get immediate value by deploying SAP HANA on the AWS cloud computing platform.
• Best practices and reference guides to help you.
• Customer success stories, including the Women’s Tennis Association (WTA).
11. A key enabler to the global economy for over 40 years,
SAP is uniquely positioned to help the world run better
At the global level
Helping customers optimize resources and
protect the environment
At the business level
Helping companies harness data to stay
ahead of change and innovate for growth
At the personal level
Helping people have a greater voice and live
better lives by personalizing engagement
SAP mobile solutions reach 97% of the
world’s mobile subscribers via text
messaging.
SAP customers represent 98%of the
top 100 most valued brands in the world.
74% of the world’s transaction
revenue
touches an SAP system.
12. Profound changes are leading to an unprecedented
empowerment of people everywhere
We need to rethink the future.
Run business
in real time
3
Optimize
resources
1
An emerging
middle class
growing to 5
billion
will strain already
diminishing
resources
More mobile
devices
than people
will require fresh
thinking designed for
an “always-on” world
Use Big Data to
your advantage
2
Data doubling
every 18 months
will create new
opportunities and
risks for value
creation
15 billion Web-
enabled devices
by 2013
will create a universe
of intelligence
everywhere
1 billion people
in social
networks
will rewire business
and personal
boundaries
13. Imagine a new world of real-time engagement where
innovation in technology can..
… While improving
the lives of people
everywhere
Power of the individual
Improvement in people’s lives
Help companies stay
ahead of change and
innovate for growth …
Future of Business
Redefinition of business models
A better-run world
smarter, faster, simpler
15. At the heart of its innovation is SAP HANA, a completely
re-imagined platform designed for real-time business
10,000x Faster helps you process massive amounts of data,
and deliver information at unprecedented speeds
Entirely New Possibilities enables you to create previously
unimaginable applications, and to rethink and envision new ways to run your business
Dramatically Simplified IT Deployable as an on-premise appliance or
in the cloud, SAP HANA dramatically simplifies complex and expensive IT architectures
Completely Open Platform as an open, adaptable, and extensible platform
SAP HANA
a revolutionary in-memory platform
18. Real-time
Business
Scenario Real-time bonus
calculations for
consumers
Sales
Customer
Service
Customer overdue credit
calculation by product
areas
Finance and
Operations
Iterative period end
closing with new posting
into accounts constantly
Manufacturing
New ATP strategies; MRP
run for individual ATP
check/instant re-planning
IMPACT ON BUSINESS Slow Response Times | Usability Challenges | Lack Of Adaptability
IMPACT ON IT High Latency | Complexity | High Cost of Solutions
Transactional
Datastore
Data
Warehouse
Sensors
Data
Mobile
Data
Archives Social & Text Geo-Spatial
Location
Intelligence
Order
Processing
Operational
Reporting
Real-time Risk
& Fraud
Trend
Analysis
Sentiment
Analytics
Predictive
Analytics
Pattern
Recognition
Analyze
ETL
Staging
Collect
Clean-Data
Quality
Transact
Aggregate
Summarize
Communicate
Monitor
Predict
Planning
0
1
Information Processing is at a critical inflection point
Point optimization is not enough to meet the new frontiers of real-time business
19. DEEP
Complex & interactive questions
on granular data
BROAD
Big data,
many data types
HIGH SPEED
Fast response-time,
interactivity
SIMPLE
No data preparation,
no pre-aggregates,
no tuning
DEEP
Complex & interactive questions
on granular data
SIMPLE
No data preparation,
no pre-aggregates,
no tuning
REAL -TIME
Recent data, preferably real-
time
HIGH SPEED
Fast response-time,
interactivity
OR
Technology today requires tradeoff
A breakthrough in today’s information processing architecture is needed
20. CPU
STORAGE
MEMORY
Compression
PartitioningOLTP+OLAP
in column Store
Insert Only on Delta
No Aggregate tables
(Dynamic Aggregation)
Solid State Flash HDD
64bit address space
1 TB in current servers
Dramatic decline in
price/performance
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
Multi-Core Architecture
8 CPU x 10 Cores per blade
Massive parallel scaling with many blades
Logging and Backup
Next-generation Software & Hardware Architecture
Removing data processing bottlenecks using latest innovations in computing
21. ACID
Compliant Database
In-Memory
Column Store
Out
In
SQL
BICS MDX
OData
HANA
Studio
Data
Services
HS Bulk
Loader
SLT
DCX
(SAP Data)
Parallel
Calculations
Scripting
Engine
Business
Function
Library
Unstructured
(Text)
Predictive
Analysis
Library
OLAP
XS App
Server
“R” HS
Integration
Batch Transfer
SAP & Non-SAP
Extensive Transformations
Structured & Unstructured
Hadoop Integration
Near Real Time
SAP & Non-SAP
ODBC / JDBC
3rd Party Apps
3rd Party Tools
BICS
NetWeaver BW
SAP BOBJ
ODBO
MS Excel
3rd Party OLAP Tools
HTTP
RESTful services
JSON / XML
“R”
ESP
What Makes HANA the Platform of Choice?
22. What’s the Difference? Column Store vs. Row Store?
Data - 8 billion humans
Attributes:
first name
last name
gender
country
city
birthday
~ 200 bytes
Query:
How many women?
How many men?
23. Data - 8 billion humans
Query: How many women, how many men?
Row Store – Stride Access “Gender”
8B tuples x 64 byte ≈ 512 GB
Assuming a scan rate of 2MB/Sec/Core
scan with 1 core will take
256 Seconds
Table: World Population
FirstName LastName Gender Country City Birth
Data - 8 billion humans
Query: How many women, how many men?
Row Store – Complete Scan
8B tuples × 200 bytes per tuple ≈ 1.6 TB
Assuming a scan rate of 2MB/Sec/Core
A complete scan with 1 core will take
800 Seconds
Table: World Population
FirstName LastName Gender Country City Birth
What’s the Difference?
Data representation in a row store
1
2
3
8 x 109 rows
1
2
3
8 x 109 rows
24. What’s the Difference?
Data representation in a column store
Data - 8 billion humans
Column Store
Dictionary of Names, Countries, Cities…
≈ 700 MB
8 B Records × 91 bytes per tuple
≈ 91 GB
Table Size: 91GB + 700MB ≈ 92 GB
Column Store Compression 17:1
Column Table: World Population
FirstName LastName Gender Country City Birth
1
2
..
200
..
40000
..
1x106
..
5x106
..
8x106
25. What’s the Difference?
Data representation in a column store
Data - 8 billion humans
Column Store
Dictionary of Names, Countries, Cities…
≈ 700 MB
8 B Records × 91 bytes per tuple
≈ 91 GB
Table Size: 91GB + 700MB ≈ 92 GB
Column Store Compression 17:1
Query:
How many women, how many men?
8B x 2 bytes for “Gender” ≈ 1 GB
Assuming a scan rate of 2MB/Sec/Core
A complete scan with 1 core will take
0.5 Seconds
1600:1 or “stride” 512:1
Column Table: World Population
FirstName LastName Gender Country City Birth
1
2
..
200
..
40000
..
1x106
..
5x106
..
8x106
Full Column Scan on “Birthday”?
8B x for “Birthday” ≈ 16 GB
Assuming a scan rate of 2MB/Sec/Core
A complete scan with 1 core will take
8 Seconds
26. Order Country Produc
t
Sales
456 France corn 1000
457 Italy wheat 900
458 Spain rice 600
459 Italy rice 800
460 Denmark corn 500
461 Denmark rice 600
462 Belgium rice 600
463 Italy rice 1100
… … … …
Columnar Dictionary Compression
• Dictionary per column
• Uses data-driven fixed-length bit encodings
• Operations directly on compressed data, using integers
• More in cache, less main memory access
1 Belgium
2 Denmark
3 France
4 Italy
5 Spain
1 3
2 4
3 5
4 4
5 2
6 2
7 1
8 4
… …
1 7
2 5,6
3 1
4 2,4,8
5 3
Logical Table
Dictionary
5 entries, so need
3 bits to encode!
Compressed
column
(bit fields)
Inverted
index
Dictionary
Where was
order 460?
Which orders in
Italy?
27. Elimination of Aggregates
• Traditional applications use “materialized aggregates”
(tables with min/max/sum/avg…) to increase analytic performance
• These aggregates must be recomputed after data changes,
or at scheduled times
• HANA aggregates massive data-sets on-the-fly with high performance => no need to save
aggregates
• Means:
– Simpler data models and application logic,
– More up-to-date
– Less log activity
28. Other Advantages of Columnar Tables
• Scanning column data is so fast that indexes are usually not required
– Saves memory as well as index update time
• Dynamic views computed on the fly
• Very fast full column aggregations, due to encoding and partitioning
(>1 B records per second)
• Add a new column to a table without a complete table re-organization
• Very efficient projections (bit-vector operations)
• Compression reduces main-memory access
– Performance bonus due to improved cache behavior
Using SAP HANA, table data may be compressed up to 5x!*
* Data dependent, please refer to the HANA sizing guide; YMMV
29. One in-memory atomic copy of data for
Transactions + Analysis
Eliminate unnecessary complexity and latency
Less hardware to manage
Accelerate through innovation and simplification
3 copies of data in different data models
Inherent data latency
Poor innovation leading to wastage
Separated Transactions + Analysis +
Acceleration processes
SAP HANA
(DRAM)
Transact
ET
L
Analyze
ET
L
Re-think Data Management with in-memory computing
Need to eliminate redundant data copies, materialization and models
A Common Database Approach for OLTP and
OLAP Using an In-Memory Columnar
Database
Hasso Plattner
VS
Accelerate
Cache
30. Any Apps
Any App Server
SAP Business Suite
and BW ABAP App Server
JSONR Open ConnectivityMDXSQL
SAP HANA Platform – More than just a database
SAP HANA platform converges Database, Data Processing and Application
Platform capabilities & provides Libraries for predictive, planning, text,
spatial, and business analytics so businesses can operate in real-time.
SAP HANA Platform
UnifiedAdministration
Life-cycleManagement
Security
Extended Application Services
Integration Services
Deployment:
Database Services
ApplicationDevelopment
ProcessOrchestration
OLTP | OLAP | Search | Text Analysis |Predictive | Events | Spatial | Rules | Planning | Calculators
Processing Engine
Application Function Libraries & Data Models
Predictive Analysis Libraries | Business Function Libraries | Data Models & Stored Procedures
Data Virtualization | Replication | ETL/ELT | Mobile Synch | Streaming
App Server| UI Integration Services | Web Server
On-Premise | Hybrid | On-Demand
Supports any Device
31. Renovate existing systems while enabling future breakthroughs
Operational
Analytics
Big Data
Warehousing
Predictive, Spatial &
Text Analytics
REAL-TIME ANALYTICS
SAP HANA PLATFORM
Sense &
Respond
Planning &
Optimization
Consumer
Engagement
REAL-TIME APPLICATIONS
SAP
BusinessSuite
SAP
BusinessOne
40+ HANA Apps,
Accelerators
& RDS
StartUps
&
ISV Apps
Operational
Datamarts
Enterprise Data
Warehouse &
BW on HANA
SAP HANA Platform
Administration
Extended Application Services
Integration Services
Deployment:
Database Services
Development
Processing Engine
Application Function Libraries & Data Models
On-Premise | Hybrid | On-Demand
32. Consumer Engagement Applications
Game-changing innovation with new applications and business models
Real-time
Engagement for
consumers
Real-time
insights for
enterprise
Generate real-time consumer
insights
Deliver personalized, engaging
experiences
Create more responsive business
with precision targeting
• HTML-5 support
• Mobile integration
• Consumer-grade usability
• OLTP + OLAP real-time Processing
• Sentiment Intelligence
• Predictive analytics
SAP HANA
PLATFORM
33. Sense & Respond Applications for Internet of Things
Faster execution by adjusting to signals in the business environment
Detect and analyze data trends by
aggregating sensor data
Benefit from more energy efficient
logistics, transforming retail
distribution
Increase quality of life through
intelligent buildings, robots, cars
and cities
• Event stream processing (ESP)
• No data preparation
• RFID Integration
• Embedded data processing
• Machine Learning
• Spatial Processing
Smart Cities
Smart Automobile
Smart Equipment
Smart Logistics
Smart House
Smart Vending
Connected Cars
34. Planning and Optimization Applications
Faster execution to adjust to changes in the business
Sales and Operations Planning
Business Planning
and Consolidation
Enable iterative period end closing
with continuous posting into
accounts
Cash forecasting management
Optimize procurement,
manufacturing, transportation
without limits
• In-memory stored procedures
• Integrated Planning and Calculation engines
• Predictive Analytics and Business Functions
• Recent data, preferably real-time
• Supporting complex questions on interactive
data
• Built-in Spatial Processing
35. SAP Business Suite
powered by SAP HANA
SAP HANA PLATFORM
SAP ERP SAP CRM SAP SCM SAP SRM
Smarter business
innovations
Unlock new growth opportunities
before your competitors do
Faster Business
Processes
Drive your business at the speed of
the market
Simpler Business
Interactions
Empower people to decide and
act in the business moment
36. SAP
HANA
(DRAM)
Operational ad-hoc analytics and monitoring
Real-time insight into the in-the-moment business situations
Accelerate business decisions
Provides vision across entire business
process
Empower front-line employees
Provide POS data analysis as interactive
session with drill-down information
Implement real-time
fraud detection, risk management and
monitoring
Pricing Accounting
Customers Forecasting Planning
Channel Inventory
Products Suppliers
Customer
Service
Finance and
Operations
Account
Administration
• OLTP + OLAP Processing
• SAP HANA Live
• SAP smart data access – data virtualization
• Real-time data integration (Replication,
Streaming)
• Unified data modeling
• Single-query access to data
37. SAP BusinessWarehouse
Powered by SAP HANA
SAP HANA PLATFORM
Data
Manageme
nt
Data
Storage
Analytical /
Planning
Engine
DATA MODELING
SAP NetWeaver BW
QUERY REPORTING ANALYTICS
SAP BOBJ Busines Intelligence
Dramatically Improved
Performance
Improved decision making,
faster reporting, and the most
up-to-date information
Simplified Administration and
Streamlined Landscape
Reduced administration
and lower TCO
Unlock The Power of Your
Data Across The
Enterprise
Self-service access
to all information at the most
granular level
38. Predictive Analytics & Machine Learning
Transforming the Future with Insight Today
Provide Business Analysts with sophisticated algorithms to take
the next step in understanding their business and modeling
outcomes.
Perform statistical analysis on your data to understand trends
and detect outliers in your business.
Build models and apply to scenarios to forecast potential future
outcomes
Combine, manipulate and enrich data to apply it to your business
scenarios. Self-service visualizations and analytics to tell your
story
• OLTP + OLAP Processing
• SAP HANA Live
• SAP smart data access – data virtualization
• Real-time data integration (Replication,
Streaming)
• Unified data modeling
• Single-query access to data
39. SAP HANA Spatial Processing
Develop and deploy spatially-enabled analytics and applications
Transaction Data Unstructured Data Location Data Machine Data
SAP HANA
Analytics Applications Visualization GIS
SAP Info Access
(HTML 5)
Mobility
REAL-TIME DATA
SPATIAL DATA
BUSINESS DATA
OLTP Analytics Planning Predictive Text Spatial
Geo-
Services
Geo-
Content
Columnar
Spatial
Processin
g
Calc
Model /
Views
Spatial
Functions
Spatial
Data
Types
Real-time
high-performance
spatial processing
Store, process,
manipulate, retrieve
and share spatial data
Unified modeling
platform
Combine spatial
with business data
Geo-content
and services
40. File Filtering
Unlock text from binary documents
Ability to extract and process unstructured
text data from various file formats (txt, html,
xml, pdf, doc, ppt, xls, rtf, msg)
Load binary, flat, and other documents
directly into HANA for native text search
and analysis
Native Text Analysis
Give structure to unstructured textual
content
Expose linguistic markup for text mining
uses
Classify entities (people, companies,
things, etc.)
Identify domain facts (sentiments, topics,
requests, etc.)
Supports up to 31 languages for linguistic
mark-up and extraction dictionary and 11
languages for predefined core extractions
SAP HANA Text Analysis
Extract information from documents. Perform text analysis on unstructured data
SAP
HANA
Text Analysis
41. Renovate existing systems while enabling future
breakthroughs
Operational
Analytics
Big Data
Warehousing
Predictive, Spatial &
Text Analytics
REAL-TIME ANALYTICS
SAP HANA PLATFORM
Sense &
Respond
Planning &
Optimization
Consumer
Engagement
REAL-TIME APPLICATIONS
SAP
BusinessSuite
& SAP
BusinessOne
30+ HANA Apps,
Accelerators
& RDS
StartUp & ISV
Apps
Operational
Datamarts
EDW on HANA
(BWonH)
SAP HANA Platform
Administration
Extended Application Services
Integration Services
Deployment:
Database Services
Development
Processing Engine
Application Function Libraries & Data Models
On-Premise | Hybrid | On-Demand
42. Uncover value
Create breakthroughs
Experience simplicity
INNOVATIONS
PREVIOUSLY UNFEASIBLE
• Real-time genome analysis
• Instantaneous fraud detection
• Predictive maintenance
• Optimize procurement, manufacturing, transportation
• Real-time MRP with instant re-planning
SIMPLICITY
PREVIOUSLY UNACHIEVABLE
• Transactions and analysis in one
system
• Efficiently analyze structured and
unstructured data
• Fewer systems needed
• Hardware cost savings
• Less DBA involvement needed
SAP HANA
In-Memory
Transaction & Analysis
directly In-Memory
VALUES
PREVIOUSLY UNATTAINABLE
• Iterative period end closing
• Cash forecasts/management
• Real-time offer calculation
• In-moment sales forecast
• Self-service apps with
instantaneous response
• Interactive POS data analysis
44. Over 18 Joint SAP & AWS Solutions
• SAP Cloud Appliance Library: http://www.sap.com/pc/tech/cloud/software/appliance-library/index.html
• SAP HANA One on the AWS Marketplace https://aws.amazon.com/marketplace/
• SAP HANA AWS Infrastructure as a Service Offering to 1.22TB http://marketplace.saphana.com/
• SAP BW Powered by SAP HANA Trial Offer - Link
• SAP on AWS information on the SAP Home Page on AWS.com: http://aws.amazon.com/sap/
45. HANA on AWS - Start Small and Scale As Needed
Try Develop Run
• Start with SAP BW on
HANA Trial for 30 days
• Get set up in less than 30
minutes
• Pre-built content and
sample data
• Use the system as-is or
load your own data and
objects
• Built-in tutorials and
community support
• Choose SAP HANA
developer edition or
SAP HANA One
• Develop, test, and demo
applications on top of the
SAP HANA platform
• Easily accessible and
rapidly deployable
• Pay for only what you use
• Community Support
• Two options for
production workloads:
• SAP HANA One to
instantly deploy a single
instance of SAP HANA
• SAP HANA (BYOL) for
real-time provisioning on
AWS using existing SAP
HANA licenses
• Various support options
available
47. Customer
Data Centers
VPN or
Direct Connect
Virtual Private Cloud
SAP HANA Disaster Recovery (DR) on AWS
DR
ECC
BWBW
ECC
PRD
SAP production (PRD) landscape
runs in customer’s own datacentre
SAP development & quality
assurance landscape runs on AWS
SAP HANA
Appliance(s)
HANA
DB
SAP HANA System
Replication (Async)
48. Customer
Data Centers
VPN or
Direct Connect
Secure
connectivity
between
datacentre & AWS
Virtual Private Cloud
Hybrid HANA Deployment – Customer Data Centre & AWS
DEV QAS
ECC
BW
ECC
BW
BW
ECC
SRM
PRD
SAP production landscape runs in
customer’s own datacentre
SAP development & quality
assurance landscape runs on AWS
SAP HANA
Appliance(s)
HANA
DB
HANA
DB
49. Virtual Private Cloud
Full SAP HANA Deployment on AWS
DEV QAS
Customer runs DEV, QAS, & PRD on AWS
PRD
VPN or
Direct Connect
Secure
connectivity
between LAN &
AWS network
Customer
LAN
ECC
BW
ECC
BW
HANA
DB
HANA
DB
ECC
BW
HANA
DB
50. Virtual Private Cloud
SAP HANA for Big Data Analytics
VPN or
Direct Connect
Secure
connectivity
between LAN &
AWS network
Customer
LAN
ECC
BW
BW
HANA
DB
SAP
BI
Amazon EMR
+
51. SAP HANA Scalability Test for
SAP BW Using In-Memory Data Fabric
111 SAP HANA Instances
(1,776 CPU Cores)
8M Rows loaded per second
(60 Billion Total)
220ms single node query
(600 Million Rows)
330ms for federated query
(60 Billion rows)
Throughput of 3 million queries
per hour
Additional Details: http://bit.ly/scale-hana-aws
54. Amazon EC2 Cluster Compute Instances for SAP HANA
2 x Intel Xeon E5-2680 v2 processors
(Ivy Bridge)
32 vCPUs with hyperthreading
64-bit
60 GB RAM
10 Gigabit Network
Enhanced Networking
2 x Intel Xeon E5-2670 processors
(Sandy Bridge)
32 vCPUs with hyperthreading
64-bit
244 GB RAM
10 Gigabit Network
NUMA and Turbo Support
c3.8xlarge cr1.8xlarge
2 x Intel Xeon E5-2670 v2 processors
(Ivy Bridge)
32 vCPUs with hyperthreading
64-bit
244 GB RAM
10 Gigabit Network
NUMA and Turbo Support
Enhanced Networking
r3.8xlarge
HANA One SAP HANA Infrastructure Subscription
55. SAP HANA Deployment Methods
AWS Global Infrastructure
AWS QuickstartAWS Marketplace
SAP Cloud Appliance
Library
AWS API’s
AWS CloudFormation
Developer Edition / Trials BYOL (Multi-Node)HANA One
SAP HANA Marketplace
SAP
HANA
57. SAP and Women’s Tennis Association (WTA)
Solution Overview
Court
Cameras
Umpires
Player
Data
Journalists
Players &
Coaches
Fans
SAP WTA
Player
Analytics
Powered by SAP HANA
Data Sources Mobile Apps
SAP HANA One
SAP Data Services
SAP BusinessObjects BI
58. Kellogg Uses AWS to Save $900,000 over 5 Years Over Using On-
premises Infrastructure
Kellogg produces breakfast foods for more than 180
companies worldwide, with annual revenue of almost $15 B.
Using AWS saves us
$900,000 in infrastructure
costs alone, and lets us run
dozens of simulations a day
so we can reduce trade
spend. It’s a win-win.
• Needed a better way to track and model promotional
costs (“trade spend”) to improve the bottom line—and
needed to be able to run more than 1 trade-spend
simulation/day
• Running SAP Accelerated Trade Promotion Planning
(TPM) – Powered by SAP HANA
• By using SAP HANA on AWS, Kellogg estimates it
will save $900,000 over 5 years versus traditional on-
premises infrastructure alternatives
• Increased business agility: Company can run dozens
of trade spend simulations each day, and decreases
deployment time by 30x
• Leveraged existing SAP HANA software license
investment on AWS
• Familiarity and Accessibility of the AWS platform
enabled engineers to easily apply their existing
knowledge and infrastructure skills
Stover McIlwain
Senior Director of IT Infrastructure Engineering
”
“
59.
60. “ ”
Mantis Technology Group – Internet
Software solution provider specializing in enterprise custom services for online retailers & high transaction volume provision systems
Product: Pulse Analytics – Social Media Analytics By SAP HANA One (Cloud)
Business Challenges/ Objectives
Offer rapid analysis of social media channels to track consumers and influencers
and measure brand against industry metrics
Scale its social media analytics service offering to handle ever increasing volumes
of data cost-effectively
Technical Challenges
Reduce cost of managing cluster of 18 Text Analysis XI and 3 MySQL servers
Analyze large volumes of social media data – more than 1M documents daily
up to 4M
Reduce the ETL load times to deliver real-time analysis
Benefits
Faster SAP HANA’s native Text Analysis and sentiment analysis with topic
identification
New real-time analytical capabilities allow for visual presentation of data that is
free from previous performance-based constraints
Data Architecture simplification by replacing 20+ separate servers with 1 instance
of SAP HANA One
Significant
Simplification
of Data Architecture
Moved from 23
servers to 1 Hana
One server
99% faster
Significantly
reduced ETL Load
time
6x faster
Text analysis
processing
“We can get close to an order of magnitude improvement in performance, additional headroom, access to new practical
capabilities (as a result of the performance improvements) AND… still save money!”
Doug Turner, CEO of Mantis Technology Group
61. Technical Implementation
• 1. Key SAP HANA features
• SAP HANA One: In-memory processing in the
cloud
• Native text analysis functionality in SAP HANA for
full-text indexing, fuzzy search and sentiment
analysis
• Automatic Data Indexing Capabilities
• Join Data on all dimensions as it is created
• Fuzzy Search for advanced clustering of similar
mentions
• On-premise capabilities
• 2. Technical KPIs
• Significantly reduced ETL data load
• 6x increase in query speed
• Simplification of data architecture
• 3. Implemented by Mantis Technology
Group
4. Partners
• Data Center provided by Amazon
SAP HANA Platform
• Architecture Diagram
5. Next Steps
Go-live on SAP HANA One by SAPPHIRE
Text Analysis
SocialSentimentAnalysisSocialSentimentAnalysis
Social Media
Channels
ETL
Process
Data
Mart
Collection
DB
Text
Analysis
Previous Architecture Diagram
HANA Architecture Diagram
Social Media
Channels
62. “We gather huge amounts of data from the field every second. For us, Business Intelligence is not about yesterdays or last week report,
it's about NOW… In our industry' it's hard to attract and retain highly qualified dedicated employees. Our highly advanced mobile
applications grant the truck driver sense of pride. They feel they contribute to our service mantra in a visible way. They do not perceive
themselves as "blue-collar workers" anymore.“
Dror Katz, Katz Logistics CEO
“ ”
Mobideo – Professional Service
First startup to bring productive customer to SAP HANA One
Product: Provides real time analysis using Joint Solution by Mobideo and SAP
HANA ONE
Business Challenges/ Objectives
Deploy easy access to information in real-time
Ensure the compliance with protocols
Deploy the monitoring and alerts for effective management
Technical Challenges
The current systems have limited ability to provide granular visibility
Provides solution that capture and available analysis in real time.
Benefits
Main cases: Katz Group (logistic Industry) and Radwin (Telecommunications)
Improve providing real time visualization and dashboards for yours customer´s
managers.
Significant Improves on the operation management through real time monitoring
and smart alerts possible by integration with SAP HANA and local devices.
Provides the most granular level of the visibility, compliance and adaptability
across the lifecycle of the operation.
Real-Time
Monitoring and Smart
Alerts
Significant
Improvement
In the Visibility and
Performance
Analysis
Scalability
Radwin has an
extensive network
(~100 countries)
63. SAP HANA
• 4. Architecture Diagram
Technical Implementation
1. Key HANA features
Data Extracting/ Loading
Integrate HANA with Business Objects, Visual
Intelligence, Visual Enterprise
2. Technical KPIs
Significantly improved data Processing
Highly improved report performance
3. Implemented by Mobideo
Estimated Project Services
– Project Duration – Months
4. Partners
SAP HANA ONE
Data Center provided by Amazon
Solution Provide by Mobideo
SAP Business Objects
Dashboards, What-if Analysis, Analytics Reports, ad-hoc
Analysis
Mobideo Studio Mobideo Engine Mobideo Web Portal
ERP
Legacy
System
s
Others Process forms
&Support documents•
Iphone Windows
Mobile
Android Windows 7/8
64. SAP HANA on AWS “Pilot” Program Offer
• Customers may receive up to US$1,000 in AWS Promotional
Credits to evaluate SAP HANA on a much larger instance
(Amazon EC2 cr1 or r3.8xlarge Instance type)
• The credit will fund the AWS infrastructure costs for customers
to trial SAP HANA through a choice of deployment methods:
– The SAP Business Warehouse (BW) Trial powered by SAP
HANA on AWS or the SAP HANA Infrastructure
subscription offering-both offered and available through
SAP
– Or if the customer has their own license of SAP HANA,
they may leverage it in a “BYOL” model and use the SAP
HANA on AWS Quick Start Reference Deployment Guide
as a tool to setup and run it themselves on the AWS Cloud
• Learn more about the Pilot offer, including terms and how to
apply for up to US$1,000 in AWS Promotional Credits at
http://aws.amazon.com/sap/saphana/pilot/
65. Where to Find SAP HANA on AWS Resources
Latest updates
How to Get Started
Deployment Information
Support Information
SAP HANA on AWS Implementation
and Operations Guide
Contact us: saphana@amazon.com
http://aws.amazon.com/sap/saphana/
SAP HANA in the AWS Cloud Quick Start Deployment Guide
http://aws.amazon.com/quickstart/
66. What is your cloud strategy?
How do you get there?
What are the risks and rewards?
What is the business case?
Discussion and Next Steps