SAP experience Day SAP BW/4HANA. 21 marzo 2018
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1 SAP experience Day SAP BW/4HANA 21 marzo 2018
2 SAP BW/4HANA The Universal data warehouse Nicola Bertini, Senior Presales Specialist Database & Data Management, SAP Italia
3 Disclaimer The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. Except for your obligation to protect confidential information, this presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or any related document, or to develop or release any functionality mentioned therein. This presentation, or any related document and SAP's strategy and possible future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The information in this presentation is not a commitment, promise or legal obligation to deliver any material, code or functionality. This presentation 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. This presentation is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this presentation, except if such damages were caused by SAP s intentional or gross negligence. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
4 Why we need to talk about the data warehousing market Performance Valuable real-time results Higher Customer Expectations Scope historical data AND Predictive, agile analytics Value Improved use of previously unused data New Types Behavioral data and the Internet of Things Larger Volumes Petabytes with a two digit annual growth rate Data New Locations Cloud and data lakes
5 Are data warehouses still the appropriate solution? Performance Valuable real-time results Higher Customer Expectations Scope historical data AND Predictive, agile analytics Value Improved use of previously unused data? Data Warehouse New Types Behavioral data and the Internet of Things Larger Volumes Petabytes with a two digit annual growth rate Data New Locations Cloud and data lakes
6 What is an Enterprise Data Warehouse? Functions of the Enterprise Data Warehouse (EDW) Analytics Business Intelligence, Predictive, Planning Characteristics Consolidates data across the enterprise Standardized data model Supports decision making Big Data Hadoop Streaming Data Warehouse Single Point of Truth Virtual Access Batch (ETL) Real-time Data Sources SAP, non-sap, On premise, Cloud Feeding external systems Planning & Forecast Main Tasks Define common semantics Harmonize data values Establish a single version of truth Provide a single, comprehensive source of current and historical information Keep copy of source data to ensure independency of source and support the unknown
7 SAP Offering: Next Generation Data Warehousing Landscape SAP BW/4HANA and Native SQL Scenarios Data Warehouse SAP Business Warehouse SAP BW/4HANA native SQL Data Warehouse Application Integration Processing Database Platform
8 SAP Data Warehousing Approaches Application driven approach, SAP BW/4HANA as premium DW application with integrated services SAP BW/4HANA SAP BW/4HANA is an application offering all required data warehousing services via one integrated repository SCHEDULING & MONITORING OLAP MODELING LIFECYCLE MANAGEMENT PLANNING ETL No additional tools for modelling, monitoring and managing the data warehouse required, but can be integrated Platform SQL driven approach, with loosely coupled tools and platform services, logically combined SQL driven approach Database approaches require several loosely coupled tools to fulfill the necessary tasks with separate repositories SCHEDULING & MONITORING OLAP MODELING LIFECYCLE MANAGEMENT PLANNING ETL A combination of tools (such as best of breed) used to build the data warehouse Platform
9 The Three Approach-Strategy for Data Warehousing Data Warehouse SAP BW/4 approach SAP Business Warehouse SAP BW/4HANA native SQL Data Warehouse SQL approach (extendable by third-party-tools) Application Integration Processing Database Platform Mixed approach
10 SAP BW/4HANA The Next Generation Data Warehouse SAP BW 7.3 powered by SAP BW 7.4 powered by SAP BW 7.5 powered by SAP BW/4HANA Starter Add-on Performance optimization Simplification and Virtualization Simplification, HANA platform integration Big Data scenarios For SAP BW/4HANA customers only Use transfer tools to make system ready for SAP BW/4HANA Requires SAP BW 7.5 SP 4 or higher Introducing SAP BW/4HANA The Next Generation Data Warehouse Built for Cloud and on premise Logical Data Warehousing Internet of Things Integrates with Big Data
11 SAP BW/4HANA The Next Generation Data Warehouse Announcing SAP BW/4HANA is a new data warehouse solution is highly optimized for solves analytics problems in seconds that take other systems days accelerates solution development means you have one version of the truth is ready for the Internet of Things at petabyte scale
12 SAP BW/4HANA Design Principals High Performance Openness Simplicity Modern Interface Conversion x faster query performance Easier access to all information Reduced development efforts New user interface for all users Powerful transition tools Leverage huge amounts of data in real time for competitive advantage Work with HANA in BW mode, or in native SQL mode, or both Get up and running sooner and keep running at lower cost Simplify access for everyone, not just database experts Convert models, flows, and data from SAP BW to SAP BW/4HANA
13 SAP BW/4HANA Values business agility cloud ready modern data warehousing Flexibility to compete in real time and adjust to changing requirements Deploy or prototype on a cloud that grows with your business High performance, futureproof platform for all new challenges
14 SAP BW/4HANA: The Solution for Universal Data Warehousing A simpler, faster, and more agile data warehouse DATA WAREHOUSING Data Acquisition Data Modeling Objects & SAP BW/4 HANA Data Modeling Tools Analytic Open Interfaces Warehousing Business Planning & Consolidation * APPLICATION DEVELOPMENT ADVANCED ANALYTICAL PROCESSING* DATA INTEGRATION & QUALITY Web Server JavaScript Spatial Graph Predictive Search Data Virtualization ELT & Replication Fiori UX Graphic Modeler Application Lifecycle Management Text Streaming Series Business Analytics Analytics Data Functions Data Quality Hadoop & Spark Integration Remote Data Sync DATABASE MANAGEMENT Columnar OLTP+OLAP Multi-Core & Parallelization Advanced Compression Multi-tenancy Multi-Tier Storage Data Modeling Openness Admin & Security High Availability & Disaster Recovery * Additional license might be required
15 SAP BW/4HANA: The Solution for Universal Data Warehousing A simpler, faster, and more agile data warehouse DATA WAREHOUSING SAP BW/4 HANA Data Acquisition Data Modeling Objects & Data Warehousing Modeling Tools Analytic Open Interfaces Business Planning & Consolidation * APPLICATION DEVELOPMENT ADVANCED ANALYTICAL PROCESSING* DATA INTEGRATION & QUALITY Web Server JavaScript Spatial Graph Predictive Search Data Virtualization ELT & Replication Fiori UX Graphic Modeler Application Lifecycle Management Text Analytics Streaming Analytics Series Data Business Functions Data Quality Hadoop & Spark Integration Remote Data Sync DATABASE MANAGEMENT Columnar OLTP+OLAP Multi-Core & Parallelization Advanced Compression Multi-tenancy Multi-Tier Storage Data Modeling Openness Admin & Security High Availability & Disaster Recovery + SAP BW/4 HANA * Additional license might be required
16 High Performance In-Memory Data Warehousing Algorithm Pushdown Advanced Analytics
17 SAP BW/4HANA In-memory Data Warehousing Query all data at the speed of No Aggregates or Roll-up Processes No Performance Specific Modeling Objects Fewer Database Indexes Faster Loading and Processing
18 Process Orchestration Process Orchestration SAP BW/4HANA Algorithm Push-down SAP BW BW on AnyDB Server Data Modelling SAP BW/4HANA Server Data Modelling Significant performance gain through push-down of operations/calculations to OLAP Data Management OLAP Data Management OLAP Engine, complex query calculations (e.g. exception aggregation) Any DB Planning Planning Pushdown Planning functions (e.g. disaggregation) All processing on application server Most processing on Data management (e.g. transformation logic)
19 SAP BW/4HANA Advanced Analytics SAP Predictive Analytics SAP BW/4HANA Source Transform Target InfoProvider HANA Analysis HAP Process InfoProvider / Index Predictions Enhance data with Advanced Analytics* using HANA specific libraries (AFL), R-Script or a custom HANA procedure Predictive Text Analysis PAL R-Script Data Mining Automated Procedure (UDF, AFL) Machine Learning * Additional license might be required
20 Openness Native SQL Access Simplified Data Integration Simplified Source Systems
21 SAP BW/4HANA Native SQL Access SAP BW/4HANA SAP BW/4HANA logic and data can be exposed to Query Composite Provider Open ODS View Calculation View * Calculation View * Calculation View * Custom Calculation Views Analytics Automatic generation of views allows: SQL logic on top of generated views Combined data from native SAP HANA DataStore Object InfoObject Calculation View * Calculation View * HANA Tables/ Views * SAP BW/4HANA generated HANA view SQL access for front-end tools Generated views are part of SAP BW/4HANA lifecycle management and SAP BW/4HANA security
22 SAP BW/4HANA Simplified Data Integration SAP BW/4HANA Non-SAP Sources Adapters ASE, ECC, HANA 3 rd Party RDBMS HANA Source System EIM smart data integration real-time replication direct access Hive Facebook Excel SAP Sources ODP Source System Files Twitter SOAP Extractors SLT full load / delta load / real-time replication Operational Delta Queue (ODQ) ABAP CDS Leverages EIM to provide new data provisioning opportunities Replicate data in real-time (HANA SDI based replication or via ODP - especially with ODP-SLT) Access data virtually Load data using optimized processing RDBMS Text Structured Social Media SAP BW Business ByDesign Or automatically switch between the different methods Check full list of supported SDI sources here
23 File Upload SAP Sources/ Web Big Data All Sources SAP BW/4HANA Simplified Source Systems Classic SAP BW SAP BW/4HANA 1 2 DB Connect UD Connect Number of Source System types reduced from 10 to 4 (60% less) 3 4 SAP Data BAPI/Partner 1 HANA Source System HANA Source System for all database connectivity (non-sap data) 5 HANA Source System 2 Big Data ** ODP Source System for SAP backend systems and SLT 6 7 ODP Extractor (SAPI) 3 ODP Big Data Source System 8 9 BW Web * File Source System (for compatibility with SAP BW) 10 File 4 File * Planned ** Connectivity to Spark (SQL) destination already possible with the HANA Source System in BW 7.50 on HANA
24 Simplicity Simplified Data Structures Simplified Data Flows Simplified Data Aging Process
25 Persistency Virtualization SAP BW/4HANA Simplified Data Structures Classic SAP BW SAP BW/4HANA MultiProvider InfoSet CompositeProvider 1 CompositeProvider Number of Modelling object types reduced from 10 to 4 (60% less) 4 5 Virtual Provider Transient Provider 2 Open ODS View No complex data structures (extended star schema) 6 InfoCube Field or InfoObject based modelling 7 8 DataStore Object Hybrid Provider 3 DataStore Object (advanced) Greater control of data persistency and virtualization 9 10 PSA Table InfoObject 4 InfoObject Support for external, structured and unstructured data
26 top down Modelling bottom up Modelling top down Modelling SAP BW/4HANA Simplified Data Flows From Layered Scalable Architecture (LSA) to LSA++ Classic SAP BW (LSA) SAP BW/4HANA (LSA++) Virtualization Architected Data Marts Virtualization/ Virtual Data Marts Architected Data Mart mandatory layer Propagation Layer Staging Layer/ Corporate Memory mandatory layers Staging Layer/ Corporate Memory Propagation Layer/ Integrated DWH Open ODS Layer/ Raw DWH optional layers depending on business needs and required service level Source Source Service Level
27 SAP BW/4HANA Simplified Data Aging Process Scale SAP BW/4HANA using Data Tiering Optimization (DTO) Extension Nodes SAP IQ Hadoop Consistent approach for hot, warm and cold data Allocate temperature by partition Displace data automatically between hot, warm and cold storage Hot Data Warm Data Cold Data in-memory Allocate by adso or adso partition in-memory Extension Node with relaxed memory requirements Allocate by adso or adso partition Automatic Displacement of Data SAP IQ / Hadoop storage / SAP Vora Allocate by adso partition
28 Thank You.
29 Follow all of SAP SAP SE or an SAP affiliate company. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE or an SAP affiliate company. The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and SAP or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation, and SAP SE s or its affiliated companies strategy and possible future developments, products, and/or platforms, directions, and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, and they should not be relied upon in making purchasing decisions. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service names mentioned are the trademarks of their respective companies. See for additional trademark information and notices.
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