1139df90-0201-0010-0cb3-e2f96a400070.pdf

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

1/54

Session ID: MDM202Configuration ofMatching-Strategies for

SAP Master DataManagement

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

2/54

SAP AG 2004, SAP TechEd / Session MDM202 / 2

Contributing Speaker(s)

Christian BehreNetWeaver Product Management, SAP AG

Remo DuranteSolution Architect, SAP Deutschland AG & Co.KG

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

3/54


Learning Objectives

As a result of this workshop, you willbe able to:

understand the role of the Master Data Management

understand the architecture of the Content Integrator

understand the matching process

explain the Content Integrator settings

understand the meaning of Normalization and MatchingAlgorithm and how to adopt them

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

4/54

Overview

ArchitectureNormalization

Matching Algorithm

Implementation Considerations

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

5/54


MDM A Key Capability of SAP NetWeaver 04

SAP NetWeaver MDM

Enables companies to store,augment, and consolidate

master data with high qualityEnsures consistent distribution to

all applications and systems within aheterogeneous IT landscape

Leverages existing IT investmentsin business-critical data

Delivers vastly reduced TCO byeffective master data management

ensuring cross-system dataconsistency

Accelerates and improves theexecution of business processes

SAP NETWEAVER

ONE PLATFORM ONE PRODUCT

SAP NetWeaver

Com

positeApplication

Framework

PEOPLE INTEGRATION

Multi channel access

Portal Collaboration

INFORMATION INTEGRATION

Bus. Intelligence

Master Data Mgmt

Knowledge Mgmt

PROCESS INTEGRATION

IntegrationBroker

BusinessProcess Mgmt

APPLICATION PLATFORM

J2EE

DB and OS Abstraction

ABAP

L

ifeCycleMgmt

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

6/54


SAP NetWeaver: Delivering on the promise of ESA

SAP NetWeaver

COMPOSITEAPPLICATIONFRAMEWORK

PEOPLE INTEGRATION

Multi channel access

Portal Collaboration

INFORMATION INTEGRATION

Knowledge Mgmt Bus. Intelligence

PROCESS INTEGRATION

IntegrationBroker

Bus. ProcessMgmt

APPLICATION PLATFORM

J2EE

DB and OS Abstraction

ABAP

...

Procurement Sales Shipment

Master Data ManagementMaster Data Management

R/3 SRM Siebel i2 Legacy

P O i f SAP MDM

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

7/54


SAP NetWeaver

Enterprise Portal

Exchange Infrastructure

Application Platform

Master Data Management

BI

KnowledgeMgmt.

Process Overview of SAP MDMLoading Master Data

IILoading Master Data with Periodic Inbound Collector

Client triggers the load PUSH principleILoading Master Data with Extraction

MDM triggers the load PULL mechanism

4

3

3

Legacy 3rd Party

22

ERP CRM

222

3

4

Legacy

2

1

1

II

1

I

4

Staging4

Process Overview of SAP MDM

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

8/54


SAP NetWeaver

Enterprise Portal




BI

KnowledgeMgmt.

ERP CRM Legacy 3rd Party Legacy

3

5

?=

6

7?

CI

DatabaseStaging2

1b

1bConsolidating Master

Data from Staging (PIC)

1a

1aConsolidating Master

Data from Extraction

Valid for both

process variants

4

9

=

Process Overview of SAP MDMConsolidating Master Data

Process Overview of SAP MDM

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

9/54


SAP NetWeaver

Enterprise Portal




BI

KnowledgeMgmt.

ERP CRM Legacy 3rd Party Legacy

?=

Process Overview of SAP MDMConsolidating Master Data - Example

Ca. 95816Brown & Partner Inc. 248 Meadow Lane Drive Sacramento

CA 93860Brownes & Partner MEADOW Lane San Diego

Ca. 95819Brown Inc. 248 Meadow Lane Drive Sacramento

Demo

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

10/54


Consolidating Master Data Challenges & Solutions

How can the data from different systems be comparedat all?

How can duplicates or identicals be determined?

How can granted/may be/most probably nothits be distinguished?

How can the system itself decide what cleansing cases to automatically confirm as duplicates or identicals? present to the master data specialist to take a decision?

automatically confirm as non duplicates or identicals?

MDM cleansing capabilities provide:

Normalization capabilities to store unaligned data in a comparableformat

Object type related Matching algorithms to compare data sets Ranking on matching results to calculate matching scores

Lower and Upper Score Thresholds to pre-decide on cleansing cases

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

11/54

Overview


Matching Algorithm


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

12/54


SAP MDM 3.00 - Architecture

BI (BW 3.5)

EP 6.0

Master

Data

Clients*

*i.e. SAPERP, CRM,

SRM

Master Data Engine 3.00

master data administration process control (process chains) Inbound staging UIs logical routing

SAP Solution Manager 3.1Content Integrator 3.00

matching engine key-mapping administration

XI 3.00

technical routing structure mapping key-mapping

cache (new 3.0)

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

13/54


Content Integrator - Process Overview

Master Data Server (MDS)

Matching

GetMatchingCandidates

CalculateScore

Content Integrator (CI)

Upload

Validation

Cleansing

ID-Mapping

Normalization

GetNormalizedAttributeKeys

Global Normalizer

NormalizeObjects

Master Data Client (MDC)

BusinessPartner 1

BusinessPartner 2

BusinessPartner 5

BusinessPartner 4

BusinessPartner 3

Stag

ingArea

XML-File

Product 1

Product 2

Product 3

Product 4

RFC

The explication you can find in the notes

C t t I t t P D t il

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

14/54



Staging Area

1. Upload 2. Normalization

Content Integrator Process Details

3. Matching4. Cleansing

Validation

Mapping

readsGetNormalizedAttributeKeys

NormalizeObjects writes

reads

CalculateScoreScore TablewritesreadsID-Mapping

Table

writes

RFC XML-File

Generation ofMDS-Objects

Global Normalizer

Object StoreTable

Index Table


Comparison

writes

API

the Normalization is triggered again for the MDS Object

(stops after writing into the Index Table)

writes

MDS

API

CI

O i T bl Vi

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

15/54


Overview: Table View

MDS-Objects with the information,to what MDC-Objects they aremapped

mapped MDC-Objects

for every new process the contentis overwritten

MDC-Data that lies abovethe lower threshold with therelated calculated score

normalized and indexed MDS-Datanormalized and indexedMDC-Data

MDS-Objects with attributesMDC-Objects without attributes(exist only to hold the references)

MDC-Objects with attributes

Content end of processContent during processTable

Object StoreTable

Index Table

Score Table

ID-MappingTable

M t hi St t (C t t)

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

16/54


Matching Strategy (Context)

The Matching Strategy

contains settings to

Normalizing Algorithm

Matching Algorithm

is defined dependent on

the particular Business Objects

the requirements of the customer

is used within a Matching Context (e.g. Global Spend)

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

17/54

Overview


Matching Algorithm


Normalization: The Process (Generally)

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

18/54



Staging Area

1. Upload 2. Normalization

Normalization: The Process (Generally)

readsGetNormalizedAttributeKeys

NormalizeObjects writes

RFC XML-File

Global Normalizer

Object StoreTable

Index Table

writes

CI

Global Normalizer Makes the data comparable Perticular settings:

Ingnore blanks, special characters or several punctuation marks Upper and lower case

Normalizing Algorithm GetNormailzedAttributeKeys

Finds the indices that are defined within the coding NormalizeObject

Indicates the data and writes them into the index table

Settings for the Global Normalizer

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

19/54



Object Type

Upper or lower case

Insert the character you want to include or exclude.

Include or exclude the characters

Enter the Reference Path

Enter the Source Path / Target Path


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

20/54



Upper or lower case

This concerns the whole content of the array. Include or exclude the characters

If you include a certain amount of characters, the other characters,that are not separately mentioned are automatically excluded.

Insert the character you want to include or excludeBe careful with the character : It must not stand in the lastposition when listing several characters. The characters have also tobe listed without any separator.

Enter the Source Path/Target PathIt corresponds to the array name of the source/target table. You canget it form the Development Guide at the Service Market Place.

Enter the Reference PathYou can get it from the object scheme displayed in the DevelopmentGuide at the Service Market Place.

Global Normalizer

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

21/54


Global Normalizer

Object model diagram of the Content Integrator

Business Partner

Reference Path

Source Path/Target Path

(source: Development Guide for Matching Strategies)


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

22/54



GetNormalizedAttributeKeys

The indices can be defined within the javacoding

You can define as an index

one array

several arrays

a certain part of an array(e.g. the first 8 characters)

Due to the fact that you can manipulatedirectly in the coding, the specification ofthe indices is very flexible.


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

23/54



NormalizeObjects

The data are indicated and written into the index table, dependentfrom the previous coding settings:

Mandant Object ID consecutive numberingof data records havingthe same ObjectID

Matched Entity ObjectID Column Key/Index ColumnValue

oneobject

NameNormalizer Customizing

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

24/54


NameNormalizer Customizing

It may contain:

The definition ofNonNameTokens

The substitution of several characters or aspecial character string

The adding/truncation of several characters

or a special character string

At the SAP Enterprise Portal a Normalizing Algorithm Customizing in XML-Format can be uploaded.

Settings for Normalizing Algorithm

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

25/54


g g g

Customizing XML file accordingto the Normalizing Algorithm.

Java Classname for


Example Normalization

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

26/54


p

Activity Example"Mnchen Traffic Corp."

1 Remove fill signs like "# _ - / \ . ,"

"Mnchen Traffic Corp"

2 Convert to upper case

"MNCHEN TRAFFIC CORP"

3 Normalize special characters according to predefinedlist (replace by AE)

MUENCHEN TRAFFIC CORP

4 (Tokenize) Cut name into tokens using list of tokenseparator: , "-"

MUENCHEN, TRAFFIC, CORP

5 Check and mark token against predefined list of non-name tokens (like CORP, BANK).


6 Check for minimum Length.


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

27/54

Overview


Matching Algorithm


Matching: The Process (Generally)

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

28/54


3. Matching4. Cleansing

reads

CalculateScoreScore Tablewrites

Index Table


GetMatchingCandidatesReads the content of the Index Table

CalculateScoreCalculates the score between the indicated data records

the score is calculated with the help of the settings in the xml-file

dependent on the defined upper and lower threshold, the results arewritten into the Score Table

objects with a score below the lower threshold are not written into theScore Table

Matching Algorithm

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

29/54


CalculateScore

Calculates the score between the indicated data records with the help ofthe settings in the XML-File

Matching Algorithm contains:

the definition of the score for theparticular attributes

conditions for the matchingcheck (e.g. check in a certainorder with a special dependence)

The score values in a existing XML-File can be replaced without changing the

Matching Algorithm.

Matching Strategy BP_300_Token_cust - Organizations

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

30/54


sum if sum 90(90 + (sum90)/10) if sum 90100 if sum > 190

Sum up

scoring points

Score

Only for ABA

BuPaavailable

Comment

+15 if match, else +0Partner/address/postalCode

+15 for first match of NameToken else+0+5 for each additional match of NameToken+5 for each match of HouseNumber

+5 for each match of NonNameToken

Partner/address/streetPartner/address/houseNumber

+10 if match, else +0Partner/address/city

+5 if match, else +0Partner/address/region

-30 if no match, else +0Partner/address/countryCode

+50 if secID and taxType match else+0+20 for each additional match of secID / taxType pairs

10 if secID no match, but taxType matches

Partner/SecondaryIDs/TaxNumber

+50 if secID and secIDType match else+0+20 for each additional match of secID / secIDType pairs

10 if secID does not, but secIDType matches

Partner/SecondaryIDs/PartnerIdentification

+25 for first match of NameToken+10 for each additional match of NameToken+10 for each match of NonNameToken

Partner/companyName

ScoringSource of Information

Matching Algorithm (Example)

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

31/54


Threshold

Original Data Reference Object

Name Mnchen Trafic CorporationStreet Brezelstrasse 7

City Mnchen

Postal Code 80331

DUNS 4711

Normalized Date Normalized Values Normalized Values Score Normalized Values Score Normalized Values Score

nameToken MUENCHEN MUENCHEN 25 MUENCHEN 25 MUENCHEN 25

nameToken TRAFIC RUECK 0 BROETCHEN 0 TRAFIC 10

non-nameToken CORP AG 0 CORP 10 CORP 10

street Brezelstrasse Brezelstrasse 15 Brezelstrasse 15 Brezelgasse 0

street number 7 17 0 17 0 17 0

city MUENCHEN MUENCHEN 10 MUENCHEN 10 MUENCHEN 10

Postal Code 80331 61525 0 61525 0 80331 15

DUNS 4711 4512 -10 - 0 4711 50

Calculated Score 40 60 120

Final Score 40 60 91

Result

Matching Canditate 2Matching Canditate 1 Matching Canditate 3

Automatic MatchCleansing CaseNo Match

Matching Result

80331

4711

Mnchen Rck AGBrezelstrasse 17

Mnchen

61525

4512 -

Mnchen Trafic CorporationBrezelgasse 17

Mnchen

Mnchener Brtchen Corp.Brezelstrasse 17

Mnchen

61525

Settings for Matching Algorithm

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

32/54


Customizing XML file accordingto the Matching Algorithm

Java Classname for theMatching Algorithm

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

33/54

Overview


Matching


Find Ways to identify Duplicates/Identicals

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

34/54


How to find records representing the same business object?

1. Using the name Name1, Name2, ..

2. Using identifying characteristics D&B no., tax no.,manufacturer part no.

3. Using other attributes Street, zip code, place

4. Built decision matrix - verify with business using real life examples

YesYes?No?NoDuplicate?

3Account Group3City3Zip Code3House No.3Street3Name

Know about the Quality of your Data

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

35/54


Examples of questions about the quality of master data

Which identifying characteristics are available in your systems and arecorrectly maintained there?

Are these characteristics always available?

What are the insignificant parts of a name for which a matchingstrategy is not required?

Which data might contain typing errors?

How big is the volume of data in the different systems? What level of similarity is required for a valid duplicate proposal?

Is there a level of similarity above which a duplicate is certain to befound?

Are the existing matching strategies sufficient to meet therequirements?

Be aware of exceptional Cases

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

36/54


Reality Check: Example - Wal-Mart as a customer

If the matching strategy is based on the name, there will be a number ofsuperfluous duplicate proposals and therefore a large amount of effort willbe required for the manual decision (clearing). This will also have a

negative effect on the system performance.

Possible Solution Adjust limit values for generating

a duplicate proposal Make Wal-Mart an insignificant

name part Adjust the matching strategy:

Are there other identifying attributesor keys that can be taken into account?

Use all Configuration Possibilities (before Developing)

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

37/54


Matching results can be influenced on 3 levels

1. Portal based configuration

build your Matching Context

choose from the out-of-the-box Normalization/Matching Algorithms

define your thresholds (lower/upper)

configure the Global Normalizer

2. XML-file based configuration

normalization (e.g. define additional non name tokens) alter the scores for the particular attributes

3. Adapt a standard algorithms, develop own algorithms

develop your own JAVA coding for normalization and/or matching define your own customizing objects for your new algorithms

follow the Matching Strategy Development Guide

Developing an new Matching Strategy

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

38/54


Steps of the development process

1. Prerequisites and Configuration of the Development Environment Install and configure the required software

SAP MDM 3.0 SP02 or higher

NetWeaver Developer Studio 2.0 or higher

2. Building your application logic

Define your project using NetWeaver Developer Studio

Import the matching API and perform recommended settings for yourproject

Design your matching and normalization strategy and implement thelogic in Java classes using the interfaces provided by the Matching API(considerMatching Strategy Development Guide)

3. Customizing and Deploying of a Matching Strategy

Define new customizing object types for matching and normalizationalgorithm and upload them on the SAP Enterprise Portal. Customizationfiles are maintained in XML format.

Fine-Tune the Normalization/Matching Algortihms

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

39/54


Test different Matching Strategies

In MDM 3.00 multiple Matching and Normalization Algorithms can beapplied on objects within one object type.

The data is loaded once, but can be used for multiple normalization and

matching processes according to different matching contexts. Generated ID-Mappings will be saved separately marked with the relevant

Matching Context.

One Matching Context can be marked for productive usage.

The whole process can be reset all relevant table content will bedeleted.

Summary

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

40/54


Content Integrator (CI) is a component of SAP Master

Data Management (MDM) to consolidate business data ina heterogeneous system landscape.

The matching process is the core process to identify

identical or similar business data objects.

Matching context provides the logic and conditions formatching processes.

With MDM some Matching Strategies are delivered.

Matching Strategies can be configured and/or developed.

Further Information

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

41/54


Public Web:www.sap.com

SAP Developer Network: www.sdn.sap.com Master Data Management

SAP Customer Services Network: www.sap.com/services/

Related Workshops/Lectures at SAP TechEd 2004MDM201 How to Use Key-Mapping in SAP MDM for Reporting LectureMDM202 Configuration of Matching-Strategies for SAP MDM Lecture

MDM203 Customizing ID Mapping in SAP Solution Manager Lecture

MDM252 Connecting a New Client-System to SAP MDM Hands-on

MDM253 SAP MDM: How to Model a New MDM Object Type Hands-on

Related SAP Education Training Opportunitieshttp://www.sap.com/education/http://service.sap.com/okp

Related MDM Documentationhttp://service.sap.com/instguides Installation and Upgrade Guides SAP

Components SAP MDM(Configuration Guides, Matching Strategy Development Guide, Description of standard

Matching Strategies)

SAP Developer Network

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

42/54


Look for SAP TechEd 04 presentations and videos on

the SAP Developer Network.

Coming in December.

http://www.sdn.sap.com/

Questions?

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

43/54


Q&A

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

44/54


Please complete your session evaluation.

Be courteous deposit your trash,and do not take the handouts for the following session.

Feedback

Thank You !

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

45/54

Overview


Matching Algorithm


Appendix

Matching Strategies

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

46/54


Matching Strategies CI 3.0

Matching Algorithm

(com.sap.ci.strategies)

Normalization Algorithm

(com.sap.ci.strategies)

Mat_300_GTIN Mat_300_GTIN_A Mat_300_GTIN_N

Mat_300_GTIN_SPN_MPN Mat_300_GTIN_SPN_MPN_A Mat_300_GTIN_SPN_MPN_N

Mat_300_ShorttextCategory_cust Mat_300_Shortt extCategory_c ust_A Mat_300_Shortt extCategory_c ust_N

Org_300_Token_cust Org_300_T oken_c ust_A Org_300_T oken_c ust_N

BP_300_Token_cust BP_300_Token_c ust_A BP_300_Token_c ust_N

TA_300_ManufacturerInfo TA_300_ManufacturerInfo_A TA_300_ManufacturerInfo_N

Organization_By_Token MDMPartnerStrategyByTokens MDMPartnerStrategyByTokens

Material_by_GTIN MDMProductStrategyByGTIN DummyMaterialNormalizationAlgo

Material_by_GTIN_MPN_SPNMDMProductStrategyByGTIN_SPN_MPN MaterialNormalizationByGTIN_SPN_MPN

TechAsset_by_ManuInfo MDMTechnicalAssetStrategyByManufacturerInfo TechnicalAssetNormalization

Please note that this document is subject to change and may be changed by SAP atany time without notice. The document is not intended to be binding upon SAP to any

particular course of business, product strategy and/or development.

Cleansing: How to Merge Manually

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

47/54


Enter one of the datacleansing case numbers


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

48/54


List of Cleansing Cases:The mapped data recordsare displayed


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

49/54


To compare the two

data, mark them andclick the button


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

50/54



7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

51/54


To merge the two objects:

Set one of the data , the other

Set the status from to

Click the button


7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

52/54



7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

53/54


Additionally you have

to enter the othercleansing case number.

No part of this publication may be reproduced or transmitted in any form or for any purpose without the express

Copyright 2004 SAP AG. All Rights Reserved

7/29/2019 1139df90-0201-0010-0cb3-e2f96a400070.pdf

54/54


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, Outlook, and PowerPoint 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, and Informix are trademarks or

registered trademarks of IBM Corporation in the United States 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, ICA, Program Neighborhood, MetaFrame, WinFrame, VideoFrame, and MultiWin are trademarks or registered

trademarks of Citrix Systems, Inc.

HTML, XML, XHTML and W3C 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.

MaxDB is a trademark of MySQL AB, Sweden.

SAP, R/3, mySAP, mySAP.com, xApps, xApp, SAP NetWeaver and other SAP products and services mentioned herein

as well as their 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 respectivecompanies. Data contained in this document serves informational purposes only. National product specifications may vary.

These materials are subject to change without notice. These materials are provided by SAP AG and its affiliated

companies ("SAP Group") for informational purposes only, without representation or warranty of any kind, and SAP Group

shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP Group 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.

Documents

1139df90-0201-0010-0cb3-e2f96a400070.pdf