201304 sap dwh strategic direction

7/30/2019 201304 SAP DWH Strategic Direction

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Data Ware ouse o ut ons romSAPStrategic Direction and Evolution


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2012 SAP AG. All rights reserved. 2

Data Warehousing Solutions from SAPOverview

Solving complex and diverse challenges

Real-time analytics

Big data

Agility

Powering sophisticated information landscapes

High-performance operational analytics

Enterprise data warehousing

Providing customer choice through complementary

and inter-operable solutions

SAP HANA Appliance

Sybase IQ

SAP NetWeaver Business Warehouse

Sybase Power Designer


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Definitions

Data Mart

Large Scale Query & AnalysisFlexible Data Marts

Simplified Maintenance

Centralized EDW

Data LineageData Consolidation

Data TransformationInformation Lifecycle Mgmt

Logical/Distributed DW

ETLGovernance

Data Distribution

Data Mart= Way to store and report on information

Data Warehouse = Ability to Manage/Integrate/Harmonize/Govern Multiple Data marts Centralized EDW = Centralized Management/Orchestration of multiple data-marts in a

single environment Logical EDW = Logical Management/Orchestration across a variety of data marts and

environments


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What is a Data Mart?

A data mart is a repository of data gathered from operational data and other sources that is designed to serve a particularcommunity of knowledge workers. The data may derive from a data warehouse or operational systems directly. The emphasis ofa data mart is on meeting the specific demands of a particular group of knowledge users in terms of analysis, content,presentation, and ease-of-use. Users of a data mart can expect to have data presented in terms that are familiar.

A data mart is a collection of subject areas organized for decision support based on the needs of a given department.

There are two main categories of data marts - dependent and independent. A dependent data mart is one whose source is adata warehouse. An independent data mart is one whose source is the legacy applications environment. All dependent datamarts are fed by the same source - the data warehouse.

Main tasks of a data mart:

Providing information specific to the needs of a certain business user group or department

Providing information ready for end-user consumption

Sourced:TechTarget


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Different Analytical Needs Leverage Appropriate Data Marts to serve Business Needs

Arch itec ted Data Mar ts (Enterpr ise BI) : Consolidated and integral part of EDW supporting decision making

on corporate data

Centrally managed by IT, standardized data models on corporateinformation

Long term requirements in terms of stability and consistency

Typically time aggregated data

Operational Data Marts (Operational Analytics):

Real Time Data and timeliness centric

Reporting on large volumes of granular, transactional data

Supporting local business execution

Higher data volatility

Agil e Data Mart s (Ad-hoc Analy sis):

Independently of the highly governed centralized corporate EDWlayers

Maximum flexibility for LoBs in data modeling and integration of LoBspecific data

Support strategic decision making in LOBs

Volatile and historical data with fluid data models

Real-Time Data Marts ( Event Based Analytics) :

Reporting on Events and Streams of Information

Defining Rules and Alerts to trigger exception based analytics

Tracking and logging Events via an audit trail and managingdeviations from audit information

Mobile consumption paradigm as key value

Near-Line Data Mart ( Query-able Archive) :

Reporting on Longer Term Trends

Reporting on Rarely Used Information for Governance / AuditPurposes

Near-LineData Marts

Query-able Archive

Archived Information

OperationalData Marts

OperationalAnalytics

DB Replication

Transactional |System of Record

Real TimeData Marts

Real TimeAnalytics

Sensor | Mobile |Social

Streams | Feeds

Transactional | Analytical |Systems of Record & Engagement

ArchitectedData Marts

AgileData Marts

Enterprise BI Ad-Hoc | Self-Service BI

ETL / ELT /Replication

Logical / Centralized Enterprise Data Warehouse(as a management framework)

ETL / ELT /Replication

Federated Queries


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What is a Data Warehouse?

Bill Inmon:The Data Warehouse is a subject-oriented, integrated, time-variant, non-volatile collection of data used to supportthe strategic decision-making process for the enterprise. It is the central point of data integration for business intelligence and isthe source of data for the data marts, delivering a common view of enterprise data.

Ralph Kimballs: A data warehouse is a copy of transaction data specifically structured for query and analysis. It is theconglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.

TDWI: Data warehousing incorporates data stores and conceptual, logical, and physical models to support business goals andend-user information needs. A data warehouse (DW) is the foundation for a successful BI program.

Main tasks of a Data Warehouse:

Integrating data from various data sources to common semantics given by the Data Warehouse data model

Harmonizing data values

Establishing a single version of truth as a source for data marts, delivering a common view of enterprise data

Providing a single, comprehensive source of current and historical information


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Logical EDW versus Centralized EDW

Logical/Distributed DW Centralized EDW

SAP Sources(Structured+Unstructured)

Non-SAP Sources(Structured+Unstructured)

Data-Marts Data-Marts

Central Data Hub

Data-Marts Data-Marts

Data Visuali zation Data Visual ization



Central EDW

Data-Marts

Data Visualization

Data-Marts

Harmonized Data

Logical Reporting Data (Cubes)


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Enterprise Data Warehousing Will Continue To Be a StrategicInvestment

Exponential Growth and IncreasingVelocity of Data

Increased Complexity of System andInformation Landscapes

Dynamic Business Requirements

Greater and More DiverseConsumption Patterns

Market Consolidation AcrossIndustries Drives M&A Activity

Focus on Internal and ExternalStakeholder Transparancy

EDW Challenges and Drivers


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SAP NetWeaver Business WarehouseAn integrated Enterprise Data Warehouse management application

Including capabilities for

Pre-defined Entity Relationship Models based on

SAP Business Suite

Agile Data modeling with

BW workspaces Non-materialized consumption of HANA datamodels in BW

Layered Scalable Archit ecture (LSA)

ETL process modeling

Real time data acquisition

Scheduling

Administrat ion l ifecycle management

High performance OLAP processing

both SAP and non-SAP sources

BW LSA ++

HANA


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A petabyte-scale elastic-compute analytics-serverthatsupports highly parallel query processing and data loading, andtunable workload management,

Supports commodity hardware and patenteddatacompression and indexing for very low Total Cost of Ownership

(TCO) Capabilities include ability to scale out with near linear

performance; native MapReduce / Hadoop integration; isolationof user communities for straightforward SLA management andsecurity; best in class in-database analytics andpredictivelibraries; advanced text search; FIPS level security.

An expanded eco-system for the support of third-partyapplications for information lifecycle management, businessintelligence and data integration, predictive analytics andsystem/data administration.

Sybase IQA proven enterprise-class columnar database IQ

Sybase IQ 15 Engine

Communications &

Security

MultiplexGridManagement

Adm

inistrationFramework

Column Indexing Sub-system

LoadingEngine

Storage Area Network

Query Engine

In-DatabaseAnalytics

Text Search

Web Enabled AnalyticsInformationLifecycleManagement

Column Storage Processor


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SAP HANAA platform for a new class of real-time analytics and applications

Real-time analytics (OLAP)

SAP Business Suite Third-party systems

SAP HANA

Real-time replication

servicesData services

Real-time apps (OLTP)

In-memory database

Planning and Calculation

EngineR & Hadoop integration

Predictive Analysis &

Business Function Libraries

Information Composer &

Modeling StudioText Search

Application Services (e.g.

HTML 5 Server)

3rd PartyBI Client

SAP NetWeaver (On Premise / Cloud )

Custom

Apps

SAP Business

Suite

SAP Business

Warehouse

SAP Big Data

App li cat ion sSAP Analytics

SAP

Mobile


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SAP HANA + Sybase IQStrategic Direction

Extend SAP HANAs processing enginewith Sybase IQ optimizer and indexinginnovations

Extend Sybase IQ Hadoop andMapReduce capabilities into SAPHANA

Next generation near-line SMARTSTORE solution for BW/SAP HANA

Customer Value

Market leading internal and externalpredictive libraries

Enterprise-wide information accesssupporting massive concurrentworkloads

Customer Value

Integration of Hadoop data andMapReduce queries with SAPHANA for Breadth AND DepthAnalysis

Customer Value

Cost effectively store Petabyte-sizeddata sets

Integrate Optimize Synthesize

Managing all OLAP and OLTP applications with close to zero application-based data redundancy by switching operations seamlesslybetween hot blades to manage 100% up-time with zero-disruption from data loads and applying fixes and new developmentsallocating data across all available storage media by hot and cold data requirements and everything in between


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SAP Data Visualization(SAP BusinessObjects BI)

Data Storage & Processing(SAP HANA Platform + Sybase IQ)

Data-Marts(Sybase PowerDesigner, HANA Model Studio, SAP BW)

SAP DeliveredData-Mart

Content(RapidMarts + RDS)

SAP Delivered EDW(SAP BW)

Custom Build EDW(Sybase PowerDesigner +

HANA Model Studio)

PartnerDelivered Data-

Mart Content(RapidMarts)

Custom BuildData-Mart

Content

SAP Enterpri se Information Management(SAP Data Services, Sybase RepServer, Sybase ESP, SLT, MDM, Informatio n Steward)



Data Mart Context EDW Context

SAP Delivered Content for

BizSuite

Present

Manage Integrate& Harmonize

Store& Process

Ingest

Build

The SAP Data Management Landscape


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Sybase IQ EDW

SAP Enterprise Data WarehousingVision

Centralized EDW(In-Memory with Temperate data)

X-Consumption of BW and HANA data models NLS - Near-Line StoragePlanned in the near future Keep Current Data In-Memory Keep Aged Data on Disk

Custom Build DW Massive Scale

Petabyte scale storageand processing of data

Sybase PowerDesignerMeta Data and datamodeling

Centralized EDW - In-Memory Packaged Data Warehouse

framework Leverage Business Content for

SAP (master data, transactiondata, semantics)

Consumption of SAP HANAData Mart models

SAP BW on HANA

SAP HANA DB

SAP BW on HANA + HANA Data Mart

Sybase IQSybase IQ

SAP BW integrated with

SAP Business SuiteCustom Build Enterprise Data Warehouses

SAP Real-Time Data Platf orm (HANA+IQ)

Today

Future

ETL/Replication

Data Marts

SAP is evolving the Data Warehouse uniting SAP BW, Sybase IQ and SAP HANA on the SAP Real-Time Data Platform

SAP HANA Data Mart

Custom Build Data marts HANA optimized for real-time

use cases Instantaneous reporting on hot

dataPlanned in the near future Consumption of BW models Sybase PowerDesigner

SAP ETL/Replicatio nSAP BW ETL

SAP HANA DB SAP HANA DB

SAP BW ETL SAP ETL/Replication


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Next generation SAP Real-time Data Platform

3rd PartyBI Client

SAP NetWeaver (On Premise / Cloud)

Custom

Apps

SAP Business

Suite

SAP Business

Warehouse

SAP Big Data

App li cat ionsSAP Analytics

SAP

Mobile

Open Developer APIs and Protocols

Comm

on

Landscape

Management

SAP Smart Data Services Platform

SAP HANA Platform

SAP Real-time Data Platfo rm

SAP Sybase ASE

Common

Modeling

SybasePowerDesigner

HADOOP

3rd

PartyDB

MPP

Scale-Out SAP Sybase SQLA

SAP Sybase ESP

SAP Sybase IQ

SAP Sybase

Replication Server

SAP Data

Services SAP MDG, MDM

SAP innovation without customer disruption


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SAPs Data Platform Supports Storing Both High Value Data As WellAs High Volume Data

SAP is a company of choice: Buy or Build! SAP BW is an integratedEnterprise Data Warehouse

management application that SAP recommends due to its tight

integration with the SAP application family (master data,harmonization, data movement, etc) For customers who want to define their own warehousing

methodology, SAP will also optimize our tooling and platform forbuilding custom warehouses

Choosing the Analytic Database

SAP BW or Custom Bui ld Warehouses?

HANA for High Value or Hot Data

Sybase IQ for Higher Volume characteristics(price/performance of in-memory and disk)

HANA+IQ for providing temperate data (tiering storage andprocessing)ataValue

Data Volume Hadoop

ASE

HANA

IQ


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Planned Innovations Future DirectionToday

SAP NetWeaver BWStrategy Overview Key Themes and Capabilities

Upcoming planned release

HANA-specific features

SAP BW and SAP HANA MixedScenarios

Not active data concept

Support of Semantic Partitioned

Objects (SPO)

Enhanced Partitioning for writeoptimized DSOs

Support for SAP BusinessObjectsExplorer

Platform independent hi ghlights

Enhanced Support of 3.x ->7.xDataflow Migration

File Download of BW meta data

DSO Planning

Future innovations

Add it ional Flexib il ity

BW/Non-BW mixed EDW environments -Managing the logical EDW

Open Operational Data Store layer

Big Data/Hadoop connector

Lower TCO with sim plif ied data modeling

Uniform modeling concepts with eclipse basedUIs

Highly reduced number of InfoProvider types foreasier data modeling

Enhanced performance and scalability

Further reduce data provisioning times

HANA optimized transformations

Data aging strategies

Conversion t ools

(Release SP 8 Q4 2012)GA since April 10th

* SAP will continue to support RDBMSplatforms

Thispresentationoutlinesourgeneralproductdirectionandshouldnotbereliedoninmakingapurchasedecision.ThispresentationisnotsubjecttoyourlicenseagreementoranyotheragreementwithSAP. SAP hasnoobligationtopursueanycourseofbusinessoutlinedinthispresentationortodeveloporreleaseanyfunctionalitymentionedinthispresentation.ThispresentationandSAP'sstrategyandpossiblefuturedevelopmentsaresubjecttochangeandmaybechanged byS AP atany timeforanyreason withoutnotice.Thisdocumentis providedwithouta warrantyofanykind, eitherexpressor implied,includingbutnotlimitedto, theimpliedwarrantiesof merchantability,fitnessfora particularpurpose,or non-infringement.SAP assumesnoresponsibilityforerrors oromissions inthis document,exceptif suchdamageswerec ausedbyS AP intentionallyor grosslynegligent.

SAP NW BW 7.30 on HANA*

HANA specific features

Performance boost for data loading,query response time and planning

HANA-optimized InfoCubes and DataStore Objects (DSO)

Simplified and faster datamodeling/remodeling

In-memory planning Support of native HANA models Simplified system landscapePlatform independent highlights

Graphical data flow modeling Semantic Partitioned Objects (SPO) Rapid prototyping of Ad Hoc Scenarios

via BW Workspaces Tighter integration with SAP Data

Services


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Thi

s i

SAP Sybase IQStrategy Overview Key Themes and Capabilities

Analyt ics Server fo r EDW and Big

Data Analytics

Shared-everything MPP with VirtualData Marts and MapReduce APIs(Native +Hadoop Federation)

Certified with SAP BusinessObjectsBIplatform and Data Services v3.x, v4.x

Analyt ics Server fo r EDW

and XLDB Analytics

Next-gen column store for XLDBanalytics w/ parallel +concurrentingestion, intelligent scale out

Near-line store/feed from/to BWand HANA

MDX API support

Optimizations/innovations w/ SAPBusinessObjectsBI platform, DataServices & Predictive Analytics

SAP BusinessObjects Services:Load Table/Client SideLoads/ELT/Upsert

SAP BusinessObjects PredictiveAnalytics: connectivity drivers

Aut onomic An alyt ics Server fo r EDW and

XLDB Analytics

Self adjusting XLDB Analytics platformincluding cloud APIs

End-to-end co-innovations / differentiationwith SAP HANA, SAP BusinessObjectsBIplatform, Data Services & Predictive Analytics

SAP BusinessObjects BI platform: FunctionLibrary support, SQL Code Optimizations

SAP BusinessObjects Data Services: Multi-node loads, insert.location

SAP BusinessObjects Predictive Analytics: In-DB Analytics

Planned Innovations Future DirectionToday(Release 15.4 Q4 2011)


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Thi

s i

SAP HANAStrategy Overview Key Themes and Capabilities

Analyt ics Plat fo rm

SAP BW on SAP HANA Additional business functions and

predictive algorithms SAP HANA Studio Modeler

enhancements

Enhanced enterprise fit andreadiness

Additional and enhanced dataprovisioning capabilities

R integration Unstructured text search Enhanced security and

authentication Hadoop Integration (DS 4.1) BPC on SAP HANA Predictive Analysis on SAP HANA Desktop visualization client for

HANA (SAP Visual Intelligence)

Expanded existing Transactional

Open Platform supp ort

Business Suite on SAP HANAreadiness

Packaged Suite Analytics

New applications on SAP HANA

Enhanced developer support

Third-party tool certification andsupport (BI - SQL, monitoring,backup and recovery, data centeroperations)

Text analytics and file filtering

Explorer support for BW on HANA

Optimized PlanningEnhancements

Odatasupport

Single sign-on with SAML

Data-at-rest encryption

Sybase Replication Server & ESPsupport

Real-Time Data Platform

New applications on SAP HANA and SAPHANA Cloud

Additional Private Cloud deploymentcapabilities for SAP HANA

Power Designer Interoperability

HANA & SAP IQ Optimization and Integration

Native integration with Hadoop

Transformed SAP Business Suite processesleveraging merged OLTP & OLAP

Additional third-party tool support (ETL, BI MDX, and more)

Further optimization & integration betweenHANA and Sybase IQ & ASE

Spatial support and integration

Planned Innovations Future DirectionToday(SPS4 Q2 2012)


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SAP Enables ChoiceWhen to choose Centralized Enterprise Data Warehouse vs Custom Build?

Enterprise Data Warehousi ng - why

Consolidate the data across the enterprise to get a consistentand agreed view on your data "Having data is a waste of time when you can't agree on an interpretation."

Combine SAP and other sources together

Standardized data models on corporate information

Supporting decision making on all organizational levels

EDWs require a Database plus an EDW tooling & capabilities

SAP NetWeaver BW provi des flexiblit y and scalable EDW capabiliti es

Highly integrated tools for modeling, monitoring and managing the EDW

Open for SAP and non-SAP systems

Agile data modeling using BW workspaces

Runs on top of HANA and other RDBMS

Easy consumption of HANA Data Mart scenarios via virtualized data access

Sybase IQ/SAP HANA provi de a real-time database platform to custom buil d an EDW Higher development and maintenance efforts than adopting a packaged approach with

SAP BW on HANA (today, there are a variety of tools with lacking integration)

SAP is building out a Real-Time Data Platform to Unify the Tooling to Build andOrchestrate Custom Data Warehouses


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Key Contacts:

DW Solution Management Scott Shepard [email protected] Daniel Rutschmann - [email protected] Erich Schneider [email protected] Yuvaraj Athur Raghuvir - [email protected] SAP BW Product Management

Lothar Henkes [email protected] Brian Wood [email protected]

DW Solution Marketing Dan Kearnan [email protected] Dan Lahl [email protected]

Sybase IQ Product Management J oydeep Das [email protected]

HANA Product Management Michael Eacrett [email protected] Ingo Brenckmann [email protected]

201304 sap dwh strategic direction

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