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SAP HANA data warehousingVision & Roadmap
Christian Tauber - Director Global Database and Technology CoE
Public
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 2Internal
Disclaimer
This presentation outlines our general product direction and should not be relied on in making a
purchase decision. This presentation is not subject to your license agreement or any other agreement
with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to
develop or release any functionality mentioned in this presentation. This presentation and SAP's
strategy and possible future developments are subject to change and may be changed by SAP at any
time for any reason without notice. This document is provided without a warranty of any kind, either
express or implied, including but not limited to, the implied warranties of merchantability, fitness for a
particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this
document, except if such damages were caused by SAP intentionally or grossly negligent.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 3Internal
Agenda
Introduction
Game Changing Trends
Why is Data Warehousing still necessary?
SAP Data Warehouse Strategy
Approaches
Components and Roadmap
Profiles of SAP HANA Data Warehouses
SQL Centric, BW Centric, Mixed Scenario
Summary
Introduction
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 5Internal
Game Changing Trends Transform the Steadily Growing Data Warehouse Market
Data People
Location – cloud, data lakes
Types – behavioral data, IoT
Volumes – PB, > 40% growth YoY
Performance – real-time results
Scope – predictive, agile analytics
Value – new & unused data (> 85%)
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 6Internal
Why is data warehousing still necessary?
Characteristics
Consolidates data across the enterprise
Standardized data model
Supports decision making
Main Tasks
Define common semantics
Harmonize data values
Establish a ‘single version of truth’
Provide a single, comprehensive source of current and historical information
S/4HANA
Business Suite
Hadoop / Data
Lakes
Non-SAP
Any App
Any DB
Analytics (BI, Predictive, Planning)
Data Warehouse“Single Point of Truth”
Cloud
Systems
(SAP,
Non-SAP)
IoT
Virtual AccessETL ELT Streaming Replication
Emb. Analytics
SAP Data Warehouse Strategy
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 8Internal
SAP Business Warehouse Today
15000+BW Customers
7000+BW 7.3 / 7.4 Customers
2500+BW on HANA Customers
Vast majority: Central EDW, harmonizing many source systems
Embedded into mission critical business processes
Constant growing HANA adoption
Strategy to run simple with SAP BW
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 8Public
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 9Internal
Data Warehousing - Two approaches
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 9Public
Application driven approach, SAP BW as EDW application with integrated services
SAP BW as a packaged application serves as a platform offering all required data warehousing services via one integrated repository
No additional tools for modelling, monitoring and managing the data warehouse required, but can be integrated
SAP BW
SAP HANA
Scheduling & Monitoring
Modeling Planning
OLAPLifecycle
ManagementETL
SchedulingTool
Modeling ToolsPlanning
Tool
MonitoringTool
Lifecycle Management Tool
ETL Tool
SQL driven approach, SAP HANA with loosely coupled tools and platform services, logically combined
Database approaches require several loosely couple tools to fulfill the necessary tasks with separate repositories
A combination of tools (such as best of breed) used to build the data warehouse
SAP HANA
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 10Internal
Current Portfolio - Assessment
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 10Public
All tools of portfolio are available and used
today, further components will be
developed.
Custom Data Warehouses / Data Marts with
these tools exists.
Tools are independent from each other with
a lack of integration for end-to-end
DW deployment and operations.
SAP Agile Data Preparation
SAP Power Designer
SAP HANA Modeler
SAP BW
SAP HANA extended appli-
cation Server
SAP HANAEIM Services
SAP Application Lifecycle
Management
SAP HANA DataWarehousingFoundation
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 12Internal
SAP HANA data warehouse (SAP HANA DW) – Strategy
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 12Public
Execution and delivery
2016 - 2018Vision
Planning and definition
2016
Analytics
(SAP BI Suite, Predictive, Planning)
SAP HANA DW SAP HANA DWSAP HANA DW
SAP DW
Foundation
SAP Power
Designer
SAP HANA
EIM
SAP BW
SAP HANA Plattform
Market presence in data warehousing
with a clear roadmap
Strong and simplified
offering with tight integration
Convergence into one technology stack
addressing BW and SQL-based DW needs
SAP DW
Foundation
SAP Power
Designer
SAP HANA
EIM
SAP BW
DW Modeling DW ETL & DM
SAP HANA Plattform
Analytics
(SAP BI Suite, Predictive, Planning)
Analytics
(SAP BI Suite, Predictive, Planning)
SAP HANA Vora
SAP HANA
Vora SAP HANA PlattformSAP HANA
Vora
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 13Internal
Development Focus
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Data Management & Processing
Data Access Services End-to-End Operations
Modeling & Metadata
SAP HANA EIM becomes the central data integration component of the SAP HANA DW
Flexible adapters for logical data warehousing covering SAP, third party and Big Data sources
Unified data processing across databases and data lakes
High performance business services, e.g. for inventory handling, planning and resource allocation
Uniform scheduling and monitoring services for SAP HANA DW data flows
Advanced data distribution services for scale out and dynamic tiering
Comprehensive life cycle services for HANA DW components
Integrated top-down modeling of DW artefacts with SAP Power Designer
Consistent release management and impact analysis across DW models
Consolidation of BW modeling objects optimized for SAP HANA
Profiles of SAP HANA DW
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 19Internal
“Profiles” of SAP HANA DW
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 19Public
SAP PowerDesigner
SAP HANA Modeler
SAP HANA ADP
HANA DW Foundation
SAP HALM
SAP HANA EIM
SAP BW Stack
BW Modeling Tools
BW Transformations
BW Provisioning
BW Transport Mgmt.
BW Process Chains
BW Query Designer
BW Authorizations
SQL centric
SAP BI, Predictive, Planning
SLT, DataServices, EIM, SRS, Extractor, SDA
Logical profiles and positioning
• SAP HANA DW offers a flexible way and strong roadmap to use the belonging components according to the requirements of a customer
• Due to different reasons customer might prefer certain combination of components:
• Existing landscape/knowledge, preferences, requirements (agile, governance)
• This will influence the recommendation for a customer architecture
• BW centric deployments
• SQL centric deployments
• Mixed deployments
SAP HANA DW BW Centric
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 20Internal
SAP HANA DW– Profile “SQL/tool centric”
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 20Public
Use Case
• Customers looking for SQL based DW
• Technical DW approach prefered
• 3rd party DW replacement
• Existing inhouse SQL knowledge
• Mainly non-SAP source system landscape
• NetWeaver / ABAP not an option
Strength• Freedom to custom built data models and data
management processes (e.g. definitions via SQL)
• Best of breed approach(e.g. 3rd party tools)
• Different modeling approaches (e.g. DataVault)
To Consider
• Integration between different tools
• Governance
• Development efforts
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 21Internal
SAP HANA DW– Profile “SAP BW centric”
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 21Public
Use Case
• Mainly SAP Source driven customer
• Existing BW customer with option to growinto HANA DW
• ABAP inhouse experience
• Guided & pattern based approach preferedover SQL
Strength• Integrated DW application with central meta
data repository
• Predefined pattern (Dimensional)
• Model driven
• Prepackaged Business Content
To Consider
• Patterns with less freedom and flexibility
• NetWeaver (ABAP) landscape required
• Replacement scenarios enhancementsaccording to HANA DW
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 22Internal
SAP HANA DW– Profile “Mixed Scenario”
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 22Public
Use Case
• Customers having BW and/or non SAP DWs in place already
• Existing SAP customers looking for a new DW implementation based on SAP HANA
• SQL and guide approach required to fullfillrequirements
Strength• Combining the strengths of both worlds
• Highly flexible implementation approach
• Tight integration between both approaches
To Consider
• Integration between different tools (e.g. multiple repositories, authorizations)
Summary
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 24Internal
SAP HANA DW – Summary
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 24Public
SAP BI, Predictive, Planning
SLT, DataServices, EIM, SRS, Extractor, SDA
SAP HANA DW as flexible and modern data warehouse framework
1. SQL centric approach is a valid and positioned scenario for data warehousing with tooling for implementation
2. SAP BW will further be developed and integrated with HANA DW components
3. Independent from starting point HANA DW components can be added and used in a mixed architecture at a later point in time
SQL centricBW centric
Mixed Scenario
HANA DW
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 25Internal
SAP HANA DW – Future-Proof Data Management Platform for Analytics
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 25Public
Serve standard SQL-based and BW-style data
warehousing in order to …
meet future demands
LDW for dynamically changing system landscapes
Cloud and hybrid deployment
Integration of any data types and Big Data technologies
Scale out to high volumes and data lakes
go beyond other DW offerings
Top out-of-the-box integration to SAP solutions –
on-premise and in cloud environments
Real-time processing power of HANA
Hadoop integration with SAP HANA Vora
HANA-based analytic business services
HANA-optimized re-usable business content
© 2016 SAP SE or an SAP affiliate company. All rights reserved.
Thank youContact information:
Christian Tauber
Director Global Database and Technology CoE
SAP Austria, Inc