BW- sap AG ppt

SAP Business Information Warehouse (BW)

Dipl. Inform. Marco Pesarese

SAP AG

© SAP AG 2003, Title of Presentation, Speaker Name / 2

Content

Introduction: The SAP company and the SAP Business Information Warehouse

From Oltp to Olap

Dimensional Modelling

Data staging

Data analyzing

BW development process


The SAP company

SAP AG in 2002 revenues: € 7.4 billion60,100 installations19,300 companies run SAPProviding 23 Industry Solutions 28,654 SAP employees (March 2003)

12 million users in 120+ countries team with us toIntegrate their business processesExtend their competitive capabilities Get a better return on information at a lower total cost of ownership

Unique Partner EcosystemMore than 1,500 partnersOverall more than 120,000 SAP partner certificates


SAP Milestones over 30 Years

mySAP.comOne-Step-Business

6,265 bill. € Revenue25,000Employees15,000 Customersin 120 Countries

R/10.3 mill. € Revenue9 Employees

R/2Mainframe

5.1 mill. € Revenue60 Employees50 Customersin 2 Countries

R/3Client/Server

424 mill. € Revenue3,200 Employees2,800 Customers in 35 Countries

mySAPBusiness SuiteSAP NetWeaverESA

7.4 bill. € Revenue28,654 Employees19,300 Customersin 120+ Countries

1999/20001972 1979 1992 2002/2003


SAP 1990-2002Million € Employees

1.000

2.000

3.000

4.000

5.000

6.000

7.000

8.000

5.000

10.000

15.000

20.000

25.000

30.000

255 362 425 563 9361.379

1.903

3.022

4.316

5.110

6.266

7.341

053 88 76 116 230 333

482775 901 796 803

1.312

0

2.138 2.685 3.1573.648

5.2296.857

9.202

12.856

19.30820.975

24.178

28.410Revenue

Profit

Employees

28,797

1,626

7,413

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002


Global and Local Customers - A Selection

http://www.siemens.de/

http://www.osram.com/default.htm

http://www.texaco.com/

http://www.visteon.com/

http://www.aventis.com/main/0,1003,EN-XX-100---,FF.html

http://www.maccentre.ru/cprices/images/monitors/Sony_logo.gif

http://www.supplyon.com/start_en_reentry.html

http://www.ms.mff.cuni.cz/EDBT2002/hp-logo.jpg

http://ens.lycos.com/ens/pics12/chevron.jpg

http://www.airbus-military.com/images/airbus_logo.gif


SAP Product Portfolio

SAP NetWeaver

SAP for <Industry>

SAP xApps

SAP xApp Resource & Program Mgmt

SAP xApp Product Definition

SAP xApp Mergers & Acquisitions

...

PackagedSolutions

Service Management for <Industry>Financial Insights for <Industry>

...

SAP for Aerospace & DefenseSAP for Automotive

...

mySAP Business Suite

mySAP ERP

mySAP Financials

mySAP HR

mySAP CRM

mySAP SCM

mySAP SRM

mySAP PLM

mySAP EnterprisePortal

mySAP Business Intelligence

mySAP Marketplace

SAP R/3 Enterprise*

mySAP All-in-One

SAP Solutions forSmall & MidsizeBusiness

SAP Business One

SAP Enterprise PortalSAP Master Data Mgmt

SAP Business IntelligenceSAP Mobile Infrastructure

SAP Exchange InfrastructureSAP Web Application Server

Industry-SpecificApplications

Entry Data RepositoryInvoice and Contract Accounting

...

...

* for installed base customers


DW Analytic Scenarios: Some examples


Business-Reporting


Report History at SAP

Roots go back to operational reporting for 30 years.

Application-specific operational reporting: Abap-programs itself were called „reports“: ~ 20.000 programs for reporting purposes.

Four generic tools developed over time:

1. SAP Query: Generation of Abap-programs. Limited sort, no olap.

2. Report-writer: FICO, Print-layout driven financial reports. Separation query definition from execution. Hierarchy support.

3. Recherche/EIS: CO, Profitability & Analysis Mini Olap with cube-alike structures. „Aspects“ & generic datastructures.

4. LIS: Logistic Information System. Data staging tools.


Report History at SAP: The Birth of BW

Winter 1996: Video-Conference with Hasso „Reporting server“ with Excel frontend.

Late summer 1997: BW 1.0. 19 developer (Walldorf). 5 pilot-customer.

2003: BW 3.x. 70 developer (Walldorf, Palo Alto, Australia, Bangalore), growing to more than 100 this year. > 6500 installations: One of the most successfull DW products in the market

Complete tool suite: Data warehouse, SAP content, olap processor, frontend reporting with Excel & web, Web Application Designer, Query Designer.

BW was the first system outside of R/3 „Light“ installation with only ~12GB.


Operational and Analysis Support

Operational Support

Details.

Current data with minimal history.

Changes triggered by events.

Minimal integration with other systems.

High normalization (for transactional integrity).

Analysis Support

Often aggregated data.

Comprehensive history needed.

Fixed from a specific point in time.

Maximum Integration with data from other systems.

Read-Only (no transactions).


Operational and Analysis Systems

Operational Systems

Complex, redundancy-free ER models for every business case.

Highly specialized programs.

Analysis Systems

One model for everything.

One set of analyzing tools for all kind of data.

Performance is more important than redundancy-free.

Massive data amount: Typical size between 100 Mbyte and 5 Tbyte.


Why it came that way?

Over the years, software system became bigger and more complex and the amount of data grew.

ER models for enterprise business scale have hundreds of logicalentries (e.g., SAP has more than 15.000 tables for R/3), which are linked together.

Millions of transactions per month made it more and more time consuming to get the data out of the system – especially, when transactions are still ongoing.


Solutions needed

Three core problems can be seen for reporting in the operational system:

a) Difficult navigation.

b) Performance.

c) Data-merge with other applications.

Part of the solution was to move all data from the transactionalsystem to a separate system, which is optimized for analysis purpose (users don‘t do transactions.)


The far side...

Centaurus A Jet (Cen A, NGC 5128): The jet originates from the vicinity of the supermassive black hole at the center of the galaxy (lower right hand corner of the image).


Transition to Dimensional Modelling

The technical aspects of operational systems became a showstopper, too:

End users can neither understand nor navigate ER models.

There is no software to usefully query a general ER model.

Low performance: Cost based optimizers are notorious to make the wrong choices (with destastrous consequences for performance).

It came out in practical work on designing databases, that thereis no optimum for best transactional design and performance.

In the middle of the 90‘s, an alternative modelling approach forhigh performance and simple navigation feature design came to life: Dimensional Modelling.


ER database design

A database should represent the current state of the real world.The world keeps changing need for state-updates.

To avoid update-inconsistencies, the ACID principle is used together with a db schema, which keeps redundancies away:

Normalized ER-models.


The Star-Schema approach

In dimensional modelling, we have facts (one big table) surrounded by dimensions (several small tables).

The fact-table has a multi-part key corresponding exactly to the single-part primary key in the dimension tables.

(In implementations, very often surrogate keys are used).

This is called the „star“-structure.

By modelling data in this way, you cannot avoid redundancy, but every kind of model in the star can be navigated in similar way and is very fast accessable.


Facts

Beside the keys, the fact table also contains numerical values (the measures): together this is called a fact.

The measures worth to analyze: An olap-engine selects and aggregates these values and delivers a multi-dimensional resultset.

Typical aggregation for all dimensions: Summation.

Exception aggregation (e.g. for time): Take last entry, average,etc.


In other words...

Dimensions answer the questions: „Who?“ „What?“ „When?“

Measures answer: „How much?“


Measure & Dimension Example

Fact 1: The city Tokio has in the year 2003 8 Mio. citizens.

Fact 2: The city Kyoto has in the year 2002 1.4 Mio citizens.

Measure: Number of citizens.

Dimensions: Space: City (measures are aggregable: sum) &

Time: Year (measures are aggregable: average (exception aggr.) )


Cube of a three-dimensional data structure


ER to Dimensional Model (DM) conversion

Connection between DM and ER: An ER diagram breaks down into several DM diagrams. DM has „business rules“, ER „data rules“.

Conversion steps:

1. Separate the ER diagram into discrete business processes. Model each one alone.

2. Select m:n relations in the ER model containing numeric and additive nonkey facts: This will be the fact tables.

3. Denormalize the remaining tables into flat tables with single-part key that connects directly to the fact table: This will be the dimensions tables.


ER to DM example


Strengths of DM

Arguments for DM in the reporting area:

Tools can make strong assumptions about the dimensional model (it is a predictable, standard framework)

It withstands unexpected changes in user behaviour.

Use of aggregates for performance-tuning.

Gracefully extensible to accomodate unexpected new data and new design desicions (e.g. adding new data columns, no data reloading. Old applications can still run).

In the business world, there is a body of standard approaches for handling common modelling situations in the business world.


Problems of the Star-Schema

For business scenarios there are some problems with the classical star-schema, e.g.:

Only max. 16 keys available for a table (covering all databases)

Although most business master data is used by several business processes, the star-schema needs to replicate all of it.

No multilingual description for the dimension-attributes

With changes of dimension-attributes over time, there is no way to take care of the old and new one values for the attributes.

All hierarchy-relations need to be modelled as attributes of a dimensiontable (in the classical approach). Beside this, some hierarchy types are not possible.


Snowflake

Snowflaking is the removal of low-cardinality attributes from dimension tables and the placement of these attributes in „secondary“ dimension tables.


BW: Something in between Star and Snowflake

1. Cluster dimensions together to have the limited-keys problem solved new table between facts and dimensions (unfortunatelly, this table is called in BW the dimensions-“D“-table)

2. Do „sidding“ of all dimension-members: No alphanumerical keys used anymore („S“-Table), replaced by surrogate ids. Needed for performance in the olap engine & simplier programming with unified structures.

3. Masterdata sharing.

4. Separate navigation from display attributes, which are used after the olap task. Cluster them into Time-depended and independed attributes: „X“, „Y“, „P“ and „Q“ tables.


InfoCube Snowflake Schema

Fact Dim

Using of DB specific features (indices, partitioning, joins,…)

Fact table

Dimension tables

Time independent characteristic values with attributesTime dependent characteristic values with attributesCharacteristic values

Attributes/hierarchies (external)


Hierarchies

Hierarchies can be modelled through dimension layout or through hierarchies on dimensions. More than one hierarchy per dimensionpossible (external hierarchies).

Hierarchies can model dimension-members on several locations, including links: More a network than a tree. Problem for the olap-engine: Aggregation should still be valid for the merging nodes.

Hierarchies can be time-/version-depended: They change during a period of time, but user expects correct merge.

Nodes can have values (e.g. costcenter).


SAP Business Warehouse: Architecture


Business Modeling

Data Flow TransparencyApplied Business StructureData Model TransparencyAutomated Administration

Hierarchies

DataModelData Flow

Process Chain

(Error-processing)


Stock Cube Example: The Cube Model


Staging

Staging is critical task: Procedure, if loading fails somewhere in the middle? Is there time enough to load while the oltp is going on with it‘s work?

Trade-off between number of aggregates & loadingtime!

Requirements: Delta-Update, Recovery & Consolidation of keys from different systems.

Several steps until data are in the cubes:

Raw-Data loading into PSA (persistent staging area).

Transfer-Rules clean the data and convert them into the correct format (e.g. number of leading zeros in customer id etc.)

Update rules apply these data for ODS (Operational Data Storage) or cubes.


Extraction, Transformation and Loading

AnwendungsspezifischAnwendungsspezifisch

ExtraktortypenExtraktortypen

Business ContentBusiness Content--ExtraktorenExtraktoren

AnwendungsunabhAnwendungsunabhängigängig

GenerischeGenerischeExtraktorenExtraktoren

KundendeKundendefiniertefinierteExtraktorenExtraktoren ((generischgenerisch))

Anwendungs-spezifischeDB-Tabellen

LIS

FI-SL

CO-PA

DB-/Tab./View

Funktions-baustein

FICOHR

SAP CRMLO Cockpit

Anwendungs-spezifischeDB-Tabellen

VerschiedeneSAP-

DB-Tabellen

InfoSet

Open for any sourceFlexible set of ETL capabilitiesIntegration to mySAP.com on application levelOpen to third-party toolsSupport of open standards


The information flow model of SAP BW

Integrated flow of dataRich transformation toolbox. Flexible and non-redundant data models.


Stock Cube Example: Data Loading

• WebService: Getting the stock price information

• PSA + ODS

• Activating

• Applying the generated transactions to the cube.


Stock Cube Example: Data Loading

Data is loaded from a WebService into the PSA, from where it goes via a transformation rule into the ODS.

Why not directly into the Cube?

Because we need to have some delta-handling:

In ODS we can define what a key is and what not, whereas in the cube everything is a key (request-number!).

Writing into ODS and then activating the delta generates two entries for the Cube:

- Minus old entry (do not delete)

- Plus new entry

Moving from F-Fact-Table into E-Fact-Table delete the null-entries

(removing the request number).


OLAP ArchitectureD

ata

Acq

uisi

tion

Com

mon

Rea

d / W

rite

Inte

rfac

e

Ope

n In

terf

ace

and

Web

Ser

vice

s

USE

R In

tera

ctio

n

AccessAccess Business LogicBusiness Logic PresentationPresentation

Database & Storage Analytical Functionality Navigation

Summarized, Dimensional data

OLAP EngineOLAP Engine BI Suite BI Suite

Granular, volatile dataODSODS

RDBMS•Data Partitioning•Indexing•Parallel Querying

Master Data

Drill-Down, Drill-Thru, Drill-AcrossPivotingWhat IfSlice and DiceGallery of ready-to-use Web Templates / Items

Table, ChartMapAlert MonitorContext Menu

Business CalculationsForecastsException ScanningAlertingQuery Pre-CalculationCachingBackground PrintingData Mining Algorithms


Olap-Analytics

Data is inside cubes Execute a query and render the resultset.

The core of every DW is the OLAP (OnLine Analytic Processor, E.F. Codd 1993) engine: It selects and aggregats the data.

Main difficulties:

Performance („keep a request always under 4 seconds“).

Optimize for business questions („currency conversion“, „elimination of int. business vol.“, „time-depended hierarchies“, „top n“, „conditions“, „planed-current-comparison“...)

SAP‘s olap engine is much more than what is defined in the literature about olap: Generalize the very different report-requirements in business.


OLAP-Functions

Navigation: Dice, Drill-down/up,Swap

Filter: Restrict (slice) characteristics to selections

Aggregation: Std: Key figure-dependant calculation formula for the aggregation of single result values. Others: Excp, Local.

Layout: Characteristics, results rows, hierarchy node position

Exception & Condition: Result-dependant selection and layout

Structuring: Hierarchical layout of characteristic values

Generic analysis functions: Formulas, Currency Transl., Elimination of Internal Business Volume, Sorting

Concepts for optimizing runtime: Aggregates, Olap-Cache

Integrated additional functions: Variables, Authorization, …


Aggregation

1. Standard aggregation is executed first. This can be set in the key figure definition. Possible types of aggregation are summation (SUM), minimum (MIN), and maximum (MAX). Minimum and maximum can be set, for example, for date key figures.

2. The aggregation of a selected characteristic takes place after the standard aggregation (exception aggregation). Possible exception aggregations available are average, counter, first value, last value, minimum, maximum, no aggregation, standard deviation, summation and variance. Cases where exception aggregation would be applied include, for example, storage non-cumulatives that cannot be summed by time, or counters that count the number of characteristics for a particular characteristic. Performance-critical: No aggregates are possible for exception-aggregation!

3. Aggregation by currency and units is executed last. If two figures are aggregated unequally with different currencies or units, the system marks this with ‘*’.

Formulas are only calculated after figures have been fully aggregated (with few exceptions like currency translation)


Performance-Issues

Access to data: Sum 100 Mbyte to one number and do this for several possible dimension-views. The result should be there in 1 - 4 seconds. Be scalable: Do a query over 2 Tbyte in the same time...

Solution: Pre-aggregate over all typical dimensions and view-states. Monitor, which queries are running and how long do they take to select good aggregates.


Designing a query

Every query can be seen as the combination of two entities:

1. A structural description of what should be seen (data-selection). This creates a new virtual cube.

2. A view which describes the layout of the resultset.


Designing a query

Dimensions are moved to different axes: Row, column, free, filter.

Filter-axis: The settings here cannot be changed during runtime (e.g., the user should see only his department).

Free-axis: Not inside the first runtime view, but can easiely be moved in by the user.

Only dimensions, no structures No cells!

At least one structure with measures needed, but maximum two structures (on different axis) One has selections/formulas.

Exception: Structure on filter-axis.

Two structures on two axes: Intersections can be used for so called „cell calculations“: Customers use this feature to implement special report numbers.

Modelling reuseable elements like calculated measures or structures.

Variables help to customize the filters at a dimension.


Stock Cube Example: A Query Definition


Executed Query in the Web as Pivot-Table


Analyze

Drill up/down/into into a dimension

Exchange dimensions in the view: Move their position on the axis, move to another axis (also free-axis moving it out).

Hierarchy navigation.

Filter on dimensions: Select members.

Sort (not breaking the hierarchies).

Define exceptions („traffic lights“) on the data.

Define conditions: Manipulate resultset by looking at the cell data.


Analyze: Cube View


Misc issues regarding queries

Technical names are used beside the internal id and description.

The internal id is not readable and recognizable for people, andthe description is language-dependend Problem in multinational companies and for debugging.


Web Application Framework

BEx Analyzer /Query Designer

BEx Web ApplicationDesigner

Web Design Tool (option)

OLAP ProcessorOLAP Processor

Web ServiceWeb Service

Charting EngineCharting Engine

Web Browser

HTLM Templates InfoProvider

BW Serverwith

SAP Web AS


SAP Business Warehouse: A usage scenario


Mobile Intelligence: PDA example

PDA specific outputHTML with reduced JavaScript for PDA devicesTransformation of style sheets into pure HTML for PDA devicesDevice-specific context menu for PDA devices

Context menuChartsNavigation and table display


Geocoding

Dimensions can have geo-coding attributes Align data into maps.


SAP BW - Business Explorer

AUTHORS ANDANALYSTS

EXECUTIVES ANDKNOWLEDGE WORKERS

INFORMATIONCONSUMERS

BUSINESS INTELLIGENCE USERS

BUSINESS INTELLIGENCE SUITE

QueryDesign

Web Application

Design

AUTHORING

REPORTING & ANALYSIS

DEPLOYMENTEnterprise

Portal Web

Desktop Mobile

DataMining

Ad-hoc Query

OLAPAnalysis

Dash-boards

TabularReports

FormattedReports


BW: Central Tool Inside SAP Applications


Perspective of data warehouses

More than just only enterprise business...


BW Development-Process

Role-in: Customers, customer-community (ASUG etc.), other SAP groups.

The art of generalizing highly different business-requirements.

SAP is a product-company: How to develop something new and still be compatible to the old systems. Difficult to develop „out of context“. Maintaining old systems is an integral part of the day-by-day work.


Development-Process: People

Two career-paths: Manager or Architect.

All (even senior-) architects and some managers are still coding.

Many nature-scientists.

Stable environment; company takes care of people by giving many (social) benefits.


Distributed development

Walldorf

Palo Alto

Sofia

Tel-Aviv

Bangalore

Sydney

Sometimes difficult to find meeting-time convenient for everyone ;-)


Our environment

Quiet environment with max. four people per office.

Much freedom to optimize workspace.

Work from home possible (internet-vpn).

Coffee-corners (often used for ad-hoc meetings).

Casual wear (Birkenstock...)

Free lunch.

(„... will work for bandwidth...“)


Development tools

Java: Perforce & Eclipse. Basis delivers it‘s own Eclipse distribution with SAP specific plugins.

Abap: Central development server Consolidationsystem Quality server.

Abap language is better than it‘s image: Optimized for large-scale database-development and complex structures. It is fast and highly scalable. Remote-debugging and tracing are said to be one of the most important success-secrets of SAP.

The R/3 basis system transports not only coding but also database changes.


Support for customers: Support Packages

BW: Every two months a support package.

Two days emergency correction time after development close.

Internal tests by developer (round-robin) and automatic tests.

Errors & solutions available via notes for customers (with attached coding corrections).


Support for customers: CSN/OSS

CSN/OSS: Message board.

Every message comes into pool (different support level: local, regional, global, development) and is then manually moved to a more specific pool.

Hiding internal notes.

Customer has (a limited) right to escalate.

Sometimes separation in New Development and Installed Base Development. Right now: Every developer must spend some time doing support.


Support for customers: Debugging

From csn access to the customer‘s system: By SAP-R3, rfc, PCanywhere or even netMeeting.

The backend has a complete IDE.

Build-in trace of every program step possible.

Debugging in the dev- or even production system.

On-the-fly code and database changes possible.


SAP/BW References

SAP-BI: http://www.sap.com/bi/

SAP-Help: http://help.sap.com/

SAP-Jobs: http://www.sap.com/company/jobs/

(current focus: „Strategic Research and Development Initiative“)

SAP Business Information Warehouse: Seemann, Schmalzridt, Lehmann. SAP Press, ISBN: 3-934358-41-1

Mastering the SAP Business Information Warehouse: Kevin McDonald, Andreas Wilmsmeier, David C. Dixon, W.H. Inmon. Wiley, ISBN 0-471-21-971-1

http://www.sap.com/bi/

http://help.sap.com/

http://www.sap.com/company/jobs/


DW References

Data Warehouse Systeme – Architektur, Entwicklung, Anwendung: Andreas Bauer, Holger Günzel (Hrsg.). dpunkt.verlag, ISBN: 3-932588-76-2 (good technology overview with comprehensive reference chapter)

The Data Warehouse Toolkit: Ralph Kimball, Wiley, ISBN: 047115337-0

OLAP - Grundlagen, Modellierung und betriebswirtschaftliche Lösungen: Karsten Oehler, Hanser Fachbuch, ISBN: 3446213090

OLAP – Multidimensionale Datenbanken: Nils Clausen, Addison-Wesley, ISBN: 3-8273-1402-X


Misc. Online-References

Ralph Kimball‘s online articles 1995-1998 in DBMS: http://www.dbmsmag.com/artin303.html#A000024

Java-Jolap: http://www.jcp.org/en/jsr/detail?id=69

MS-Mdx: http://msdn.microsoft.com/library/default.asp?url=/library/en-us/dnolap/html/sqlolap.asp

The Data Warehousing Information Center (link collection):http://www.dwinfocenter.org/

Bill Inmon: http://www.inmoncif.com/

Nigel Pendse: http://www.olapreport.com/

http://www.dbmsmag.com/artin303.html#A000024

http://www.jcp.org/en/jsr/detail?id=69

http://msdn.microsoft.com/library/default.asp?url=/library/en-us/dnolap/html/sqlolap.asp

http://msdn.microsoft.com/library/default.asp?url=/library/en-us/dnolap/html/sqlolap.asp

http://www.dwinfocenter.org/

http://www.inmoncif.com/

http://www.olapreport.com/


Q & A

Any questions?


The End.


Copyright 2003 SAP AG. 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 AG. The information contained herein may be changed without prior notice.

Some software products marketed by SAP AG and its distributors contain proprietary software components of other software vendors.

Microsoft®, WINDOWS®, NT®, EXCEL®, Word®, PowerPoint® and SQL Server® are registered trademarks of Microsoft Corporation.

IBM®, DB2®, DB2 Universal Database, OS/2®, Parallel Sysplex®, MVS/ESA, AIX®, S/390®, AS/400®, OS/390®, OS/400®, iSeries, pSeries, xSeries, zSeries, z/OS, AFP, Intelligent Miner, WebSphere®, Netfinity®, Tivoli®, Informix and Informix® Dynamic ServerTM are trademarks of IBM Corporation in USA and/or other countries.

ORACLE® is a registered trademark of ORACLE Corporation.

UNIX®, X/Open®, OSF/1®, and Motif® are registered trademarks of the Open Group.

Citrix®, the Citrix logo, ICA®, Program Neighborhood®, MetaFrame®, WinFrame®, VideoFrame®, MultiWin® and other Citrix product names referenced herein are trademarks of Citrix Systems, Inc.

HTML, DHTML, XML, XHTML are trademarks or registered trademarks of W3C®, World Wide Web Consortium, Massachusetts Institute of Technology.

JAVA® is a registered trademark of Sun Microsystems, Inc.

JAVASCRIPT® is a registered trademark of Sun Microsystems, Inc., used under license for technology invented and implemented by Netscape.

MarketSet and Enterprise Buyer are jointly owned trademarks of SAP AG and Commerce One.

SAP, R/3, mySAP, mySAP.com, xApps, xApp and other SAP products and services mentioned herein as well astheir respective logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries all over the world. All other product and service names mentioned are the trademarks of their respective companies.


Copyright 2003 SAP AG. Alle Rechte vorbehalten

Weitergabe und Vervielfältigung dieser Publikation oder von Teilen daraus sind, zu welchem Zweck und in welcher Form auch immer, ohne die aus-drückliche schriftliche Genehmigung durch SAP AG nicht gestattet. In dieser Publikation enthaltene Informationen können ohne vorherige Ankün-digung geändert werden.

Die von SAP AG oder deren Vertriebsfirmen angebotenen Softwareprodukte können Softwarekomponenten auch anderer Softwarehersteller enthalten.

Microsoft®, WINDOWS®, NT®, EXCEL®, Word®, PowerPoint® und SQL Server® sind eingetragene Marken der Microsoft Corporation.

IBM®, DB2®, DB2 Universal Database, OS/2®, Parallel Sysplex®, MVS/ESA, AIX®, S/390®, AS/400®, OS/390®, OS/400®, iSeries, pSeries, xSeries, zSeries, z/OS, AFP, Intelligent Miner, WebSphere®, Netfinity®, Tivoli®, Informixund Informix® Dynamic ServerTM sind Marken der IBM Corporation in den USA und/oder anderen Ländern.

ORACLE® ist eine eingetragene Marke der ORACLE Corporation.

UNIX®, X/Open®, OSF/1® und Motif® sind eingetragene Marken der Open Group.

Citrix®, das Citrix-Logo, ICA®, Program Neighborhood®, MetaFrame®, WinFrame®, VideoFrame®, MultiWin® und andere hier erwähnte Namen von Citrix-Produkten sind Marken von Citrix Systems, Inc.

HTML, DHTML, XML, XHTML sind Marken oder eingetragene Marken des W3C®, World Wide Web Consortium, Massachusetts Institute of Technology.

JAVA® ist eine eingetragene Marke der Sun Microsystems, Inc.

JAVASCRIPT® ist eine eingetragene Marke der Sun Microsystems, Inc., verwendet unter der Lizenz der von Netscape entwickelten und implementierten Technologie.

MarketSet und Enterprise Buyer sind gemeinsame Marken von SAP AG und Commerce One.

SAP, R/3, mySAP, mySAP.com, xApps, xApp und weitere im Text erwähnte SAP-Produkte und –Dienstleistungen sowie die entsprechenden Logos sind Marken oder eingetragene Marken der SAP AG in Deutschland und anderen Ländern weltweit. Alle anderen Namen von Produkten und Dienstleistungen sind Marken der jeweiligen Firmen.

BW- sap AG ppt

Documents

sap employees

sap milestones

sap query

examples sap ag

selection sap ag

sap companysap ag

businessreporting sap

base customers sap ag