EDW Positioning Based on the SAP Real-Time Data Platform

1. EDW Positioning
Based on the SAP Real-Time Data Platform
July, 2013

2. Typical needs in a Enterprise world
Introduction

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Types Analytics & Data Marts
Different Analytical needs and the consequences in IT architectures
Complex architecture landscapes including different kind
of Data Marts, Data Warehouses and EDWs
Operational
Data Mart
Visibility
Direct / Database
Replication
Near-line
Data Marts
(Audit / SOX)
Federated
Queries / ETL
Agile
Data Marts
Ad-Hoc | Self-
Service BI
ETL / ELT/
Replication
Data
Warehouse/
EDW
Consolidated
view
ETL / ELT /
Replication
Transactional |
System of Record
Transactional | Analytical |
Systems of Record & Engagement
Real Time
Data Mart
Real Time
Streams / Feeds
Event | Machine
ETL / ELT/ Replication
Federation of Data & Query
All sources
Predictive
Data Marts
Unstructured
Data Marts
Sentiment
Analysis
Archived
Information Social
Architecture
Information needs
Source of
information
Access method to
source data
Predictive
Analysis
Archive
Analysis
 High variety of information sources
 Extensive information needs

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Different Needs …
Different Types of Data Marts for Reporting
Characteristics of Data Marts:
• Maximum flexibility for LOBs in data modeling
and integration of LOB specific data (Agile)
• Supporting local business execution
• Support strategic decision making in LOBs
• Independently of, or sourced from the centralized corporate
EDW layers
• Reporting on large volumes of granular, transactional data
• Data latency determined by business requirements – batch
to real time
• High Volume Unevenly structured data (Big Data)
• Predictive Analysis
• Event and Streaming sources
A data mart is a collection of data coming from subject
areas organized for decision support based on the needs
of a given domain / group of users.

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Examples of Different Types of Data Marts
Business Intelligence Tools
Supplier Data
Operational
Real-time
replication and
ETL
ETL
ERP Data OtherEDW
Agile DataMartOperational DataMart
Operational Data Marts:
• Real Time Data
• Reporting on large volumes of granular,
transactional data
• Supporting local business execution
Agile Data Marts:
• Independently of the highly governed
centralized corporate EDW layers
• Maximum flexibility for LOBS in data
modeling and integration of LOB
specific data
• Support strategic decision making in
LOBs

6. © 2013 SAP AG. All rights reserved. 6
Unlock The Power of Your Data Across The Enterprise
Enterprise Data Warehousing – the single point of truth
EDW * – characteristics:
• Consolidate the data across the enterprise to get a
consistent and agreed view on your data
• Combine SAP and other sources together
• Standardized data model on corporate information
• Supporting decision making on all organizational levels
EDWs require a database plus EDW orchestration
tools:
• EDW orchestration tools are used to manage, model and
run the Enterprise Data Warehouse
• EDW orchestration tools can be shipped as an integrated
EDW application
• Custom built EDWs are based on loosely coupled
orchestration tools e.g. ETL tools, Data Modeling tools,
Monitoring tools etc.
* EDW and DW are often used interchangebly. For the
remainder of this presentation only the term EDW will be used.

7. © 2013 SAP AG. All rights reserved. 7
global
local
regional
Master Data
Management
Business Intelligence Tools
“
Planning &
Forecast
feeding
external
systems
Example of a Customer Enterprise Data Warehousing landscape
DataMart
DataMart
Master Data
Transactional Data
Example for global EDW
implementation:
Architecture to provide the base for
entire commercial business intelligence
solutions:
• Local, regional, global Data Marts
in addition to global Data Warehouse
necessary to meet business users
need
• Data Warehouse as single point of
truth with harmonized master data
to feed departmental Data Marts
and external systems with cleansed
data
• Depending on users requirements
reporting on departmental Data Mart
or Data Warehouse is possible
Data Warehouse
„Single Point of Truth“
ERP Data Supplier Data OtherCustomer Data
DataMart

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Different Approaches
What approach is right for you?
Different approaches to implement an analytical data foundation
• Using an Integrated EDW application
• Model-driven pre-packaged Data Warehouse application as a
central component
• Prebuilt Information – and process content
• Out of the box tool set for modeling, managing, operating, and
governing an EDW and its data marts
 Custom Built Enterprise Data Warehouse
• Loosely coupled orchestration tools
• Higher efforts for development and maintenance
• High flexibility to build custom data models and processes with
little enforced governance
• Open environment to easily import industry models

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Different Approaches
What approach is right for you?
• Custom built data marts without EDW integration layer
• Maximum flexibility for custom data marts specifically built for
isolated use cases
• Easy to build and fast realization time
• Low level of integration among different data marts
• Grow from custom built DMs to an EDW
• Combine custom built DMs or EDW with integrated EDW application
Combination of approaches

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Very large Data Marts
Data Volume and Complexity considerations
Enterprise Data Warehouse, Data Marts
datavolume
huge
moderate
Complexity: number of scenarios, data models, sources, … huge
• Mix of scenarios with small and
large amounts of data
• Many (100s to 10000s) of data
models
• Many (100-1000s) different data
sources
• Extremely high number of
scenarios and combinations of
scenarios
• Extremely high data volumes
• Internet scale business process
(e.g. Ebay, Amazon, …) generating
huge amounts of (sensor) data
• Fairly modest challenges regarding
semantics, consolidation, harmoni-
zation, integration with other data
Data Mart EDW
Extreme large EDW
• Few data sources
• Data mart type of setup or operational
(OLTP) analytics
• Moderate number of tables
• Moderate (need for) integrations between
data models

11. How does SAP address the needs?

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SAP Real-Time Data Platform
Addressing the architectural needs
Custom
Apps
Mobile &
Embedded
Business
Intelligence
Business
Suite
Business
Warehouse
SAP RTDP addresses the needs for a packaged
EDW framework with SAP BW, as well as custom
built EDW and Data Marts
• SAP NetWeaver BW as strategic offering for packaged
EDW frameworks
• SAP HANA as an in-memory foundation for custom built
solutions and in-memory database platform for BW
• SAP Sybase IQ as disk-based database for custom built
petabyte scale EDW and cost effective near-line storage
solution (NLS) for BW on HANA

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SAP HANA, BW on HANA, Sybase IQ
Strong individual solutions
Sybase IQ
BW on HANA
SAP HANA
SAP HANA
• Data Platform for business- or mission-critical enterprise applications
• In-Memory database for transactional and analytic workloads
• More than 1000 customers with standalone, BW or Business Suite scenarios
SAP NetWeaver BW
• More than 14000 customers referring to > 17000 productive systems
• Vast majority: Central EDW, harmonizing many source systems
• Embedded into mission critical business processes
Sybase IQ
• Recognized leader in EDW market by Gartner and Forrester Group
• Industry leading performance and scale benchmarks with 4500+ installations in 2150 accounts
• Greater than 96% customer satisfaction rates - consistently

14. © 2013 SAP AG. All rights reserved. 14
Data Modeling
• Layered scalable EDW model
• Tight integration with native HANA Data Marts
• In-Memory based OLAP features and
Planning engine
• Agile Data Marts with BW Workspaces
Scheduling & Monitoring
• Process Chains enable workload management for
data load processes across systems
• Rich monitoring capabilities via Admin Cockpit
• Support of 3rd party tools such as UC4, Tivoli
Supportability, Traceability
• Easy extensible BADI framework for data staging,
reporting and authorization
• Access statistics including Identity handling
• Possibility to trace on application logic, database
access and effect of authorizations
Reliable Data Acquisition
• Open for SAP – and non SAP systems
• Embedded ETL and Streamlined In-Memory Data
Staging processes
• Sophisticated Error Handling
• Incremental Data Provisioning capabilities
Business Content
• Enables fast implementation
• Leverages SAP’s proven knowledge in
business applications and industries
• Model-driven approach
EDW with SAP BW on HANA
Lifecycle Management & Security
• Hot- / Cold data handling for optimized resource
usage
• Compliant NLS and Archiving
• Fine-grained security model with mass handling
capabilities

15. © 2013 SAP AG. All rights reserved. 15
Data Modeling
• Entity-Relationship models
• Procedural extensions for complex views
• Support for planning operations on views
• Real-time transformation 3NF to analytic view
Scheduling & Monitoring
• DB level monitoring in SAP HANA Studio
• Explain plans for SQL statements
• No scheduling capabilities, requires additional tools
such as SAP Business Objects Data Services
Supportability, Traceability
• Technical tracing of database kernel operations
• Alerting for vital database parameters
• Integration with SAP Solution Manager
Reliable Data Acquisition
• Support for virtually any kind of data
• Support for SAP or 3rd party ETL tools
• Real time replication and event stream connection
Business Content
• Business Suite data models available as
content packages (SAP HANA Live, RDS)
• Application content available as delivery units
Lifecycle Management & Security
• Repository for design time artifacts
• Database security with user and role concept
• Privilege concept for design time and runtime
• Content lifecycle management
EDW with SAP HANA

16. © 2013 SAP AG. All rights reserved. 16
Data Modeling
• Leading open modeling tool: PowerDesigner
• High flexibility in schema definition
• Ad-Hoc SQL, structured and unstructured data
support, and integrated full text search
• In-database analytics, MapReduce API, Hadoop
and R-Integration
Scheduling & Monitoring
• Web-based SAP Sybase Control Center as DB
administration & monitoring tool
• ETL scheduling with DataServices
• Open and certified support for 3rd party monitoring
solutions
Supportability, Traceability
• Database auditing: logins, data update
timestamps, and administrative actions
• Support of multiple trace and debug levels
• Extensive set of system stored procedures for
diagnostics
Reliable Data Acquisition
• Open for SAP – and non SAP systems
• Data Services as powerful, approved ETL tool
• Open and certified support for 3rd party ETL solutions
• Real Time Data Loading via ESP and SRS
Business Content
• Prebuilt vertical Industry Warehouse Solutions
• Open and certified support for many 3rd party
applications
EDW with SAP Sybase IQ
Lifecycle Management & Security
• Built-in disk–based Information Lifecycle Management
• Role-based access control, LDAP authentication, strong
database, column, and transport layer encryption (FIPS
certified)
• New generation petabyte-scale store
• Resilient Multiplex grid architecture

17. © 2013 SAP AG. All rights reserved. 17
SAP HANA, BW on HANA, Sybase IQ - Integration scenarios
Integration scenarios:
• Tight integration between BW on HANA and native
HANA scenarios combines the strengths of both worlds
• Consumption of BW data models in HANA and
consumption of HANA models in BW
• Data staging from HANA to BW and from BW to HANA
• IQ supports NLS (multi temperature Data) for BW on
HANA and remote data access from HANA for smart
query processing
• Lower TCO by reduced data volumes in HANA and
shortened backup time frames
• Cost – and Performance optimized EDW
• Mature EDWs will leverage the capabilities of all three
components where appropriate
BW on HANASybase IQ
Packaged
EDW
framework
Custom built EDW
Tight
Integration
between BW on
HANA and SAP
HANA
SAP HANA
Smart Data
Access
Sybase IQ
as NLS for
BW
Custom built
EDW
Petabyte
scenarios Sweet Spot
for Mature
EDW

18. © 2013 SAP AG. All rights reserved. 18
Customer requires standalone Data Marts
• HANA provides maximum agility for custom built data marts
• With increasing BI maturity* customers are able to grow from HANA based Data Marts to an EDW
on HANA
Customer requires operational analytics directly on the original transactional data
• SAP HANA Live for SAP Business Suite (see appendix for more details)
Customer requires an EDW
• BW on HANA is SAP‘s strategic EDW solution and should be considered as a cornerstone for
customers‘ EDW strategy
Customer requires an EDW for very large data volumes
• Sybase IQ recommended for Petabyte scale
Customer requires an NLS solution
• Sybase IQ provides very low TCO for advanced data lifecycle management capabilities, e.g. NLS
Conclusions – Isolated view
SAP HANA
* TDWI BI Maturity Model
BW on HANA
Sybase IQ

19. © 2013 SAP AG. All rights reserved. 19
• BW on HANA and HANA Agile Data
Mart scenarios perfectly address the
needs of Central EDWs and Data Marts
• IQ is SAP‘s native NLS for BW on
HANA and is capable of storing
terabytes to petabytes of structured &
unstructured data
• Mature customer architectures will
leverage the capabilities of all three
components where appropriate
The HANA EDW
SAP HANA, BW on
HANA + IQ NLS
Conclusion – The HANA EDW
Combining the strengths of the different worlds
Sybase IQ
BW on HANA
SAP HANA

20. Thank you
Contact information:
Product Management: Lothar Henkes, Courtney Claussen, Brian Wood
Solution Management: Daniel Rutschmann
Consulting: Andreas Scholl
COE: Lars Jakob
CSA: Rudolf Hennecke

21. © 2013 SAP AG. All rights reserved. 21
Further Information
Find additional information
• www.SAPHANA.com
• Real-Time Data Platform landing page: www.sap.com/RTDP
• SAP NetWeaver Business Warehouse 7.4:
http://scn.sap.com/docs/DOC-35096
• BW on HANA FAQ: http://spr.ly/bwonhanafaq
• Roadmaps: http://service.sap.com/roadmap
Link to EDW Positioning presentation:
• http://www.saphana.com/docs/DOC-2164
• https://scn.sap.com/docs/DOC-41326

22. © 201 SAP AG. All rights reserved.
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