Getting Started with MDMPDF download from SAP Help Portal:http://help.sap.com/saphelp_nwmdm71/helpdata/en/46/93b4470ce0581ee10000000a1553f7/content.htm

Created on July 30, 2014

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Table of content

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Table of content1 Getting Started with MDM1.1 MDM Concept and Functional Components1.1.1 What is MDM?1.1.2 MDM Scenarios at a Glance1.1.3 Functional Components1.2 Key Capabilities of MDM1.2.1 Master Data Integration1.2.2 Master Data Operations1.2.3 Master Data Quality1.3 Step-by-Step Example of Harmonizing Master Data1.3.1 Preparing the Sample Data1.3.2 Preparing the MDM Repository1.3.3 Reviewing the Data Model and Administration Data1.3.4 Getting Familiar with the Business Partner Records1.3.5 Importing New Business Partner Records1.3.6 Identifying Duplicates1.3.7 Merging Duplicates1.3.8 Syndicating Business Partner Records

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1 Getting Started with MDMObjective and Target Group of this Guide

The objective of this guide is to give a high-level overview of SAP NetWeaver Master Data Management (MDM) product including its architecture and featuresand to serve as the entry point for the rest of the MDM documentation.

The target group is readers with little or no understanding of MDM who are interested in a brief introduction to the MDM product. Reading the guide and carrying outits subsequent practical exercises will familiarize you with MDM in less than a day.

Structure of this Guide

The guide is divided into the following parts:

MDM Concept and Functional ComponentsThe first part of this guide gives you an introduction to the concepts and functional components of MDM. It describes the components of an MDM systemand gives you an overview of six scenarios. Furthermore it serves as a knowledge base for the practical example which is described in the tutorial.Key Capabilities of MDMThe second part of this guide provides an overview of the functions provided by MDM in the three key capability areas of master data integration, masterdata operations and master data quality. It does not focus on procedures for performing the functions; these are described in the linked documentation.Step-by-Step Example of Harmonizing Master DataThe third part of this guide explains the key functions of MDM using a tutorial.In simple steps you learn how to load, match, and merge business partnermaster data so that you can export this data.

1.1 MDM Concept and Functional ComponentsThis part of the guide describes the basic concepts of MDM. Questions like "What is MDM", "What can it be used for?" and "What are some concrete examplesof how to use MDM?" are answered.

The short overview of the six core and business scenarios is a recommendation for how you can use MDM.

In addition this part of the guide provides an brief overview of the functional components of MDM with a rough description of how the individual components areused.

1.1.1 What is MDM?Definition of Master Data

Master data is the core data of an enterprise that exists independently of specific business transactions and is referenced in business transactions. It builds thefoundation for the smooth execution of business processes and well-informed business decisions. Master data represents business objects rather than businesstransactions and is rarely changed over a long period of time. The following objects are among a company's most important master data objects:

ProductCustomerSupplierEmployee

Companies have to be aware that there are several different views on master data. So within one company, the different areas create individual versions of amaster data record and the trading partners along the value chain also introduce additional versions. To demonstrate this, the figure below shows that the differentversions are stored in multiple systems:

The customer Jane has (except for her first name) totally different data in the call center and the ERP system.The product to be sold has three different part numbers.The vendor has two different identification numbers.

So the definition and handling of master data is a task of paramount importance for a company because:

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Master data is needed to make decisions on all company levels.Business processes throughout the entire company rely on master data.High-quality master data helps to improve the operational efficiency of a company.With high-quality master data, costs can be reduced. With a Global Spend Analysis you can negotiate better prices granted from the suppliers.

Master Data Management (MDM)

Master data management (MDM) is a technology that includes the definition of processes and responsibilities for master data maintenance. In case of distributedsystems, MDM has to support the synchronization of master data across the enterprise. In addition, MDM has to ensure the availability of master data in goodquality. MDM is the sum of all activities, processes and technical mechanisms that are required to achieve these goals.

However, MDM is not only a technology, it also requires joint efforts from different business areas as well as organizational rules and processes. So MDM is anenterprise-wide task that requires the cooperation of a company's business units which includes policies and responsibilities for managing master data.

MDM as the Foundation of Enterprise SOA

IT landscapes today are quickly moving towards dynamic environments enabled by service-oriented architectures (SOA) where specific master data strategiesplay an important role. Business processes work successfully within the context of dynamic services only if they are founded on reliable information - that is,consistent master data. Why? Because processes cannot successfully exceed application boundaries if they do not know how key master data should betranslated and interpreted in these systems. Prior to shifting to a service-oriented architecture, companies must cleanse their data across system boundaries;otherwise business processes will get stuck on these issues.

SAP NetWeaver Master Data Management (MDM)

SAP NetWeaver MDM fits the above-mentioned description of an MDM solution. It ensures that questions about master data as specified below are answered sothat business processes can run smoothly and business decisions are well informed:

SAP NetWeaver MDM offers the capabilities and functions to handle master data according to a company's needs. These capabilities and functions can be usedin the following ways:

SAP NetWeaver MDM is used to aggregate master data from across the entire system landscape (including SAP and non-SAP systems) into a centralizedrepository of consolidated information. In this context, MDM also acts as a central hub and allows the enrichment of data via third-party integration. Theconsolidated master data is a prerequisite for sound business operations and reliable company-wide reporting.High information quality is ensured by syndicating harmonized master data that is globally relevant to the subscribed applications. In these remoteapplications, master data can be enriched with locally relevant information.A company's quality standards are supported by ensuring the central control of master data, including maintenance and storage. Centrally created masterdata can be syndicated to remote systems as required using distribution mechanisms.In addition to the above mentioned ways, there are many other ways to use SAP NetWeaver MDM. The specific usage depends on the main focus of thetask that has to be fulfilled.

More information:

MDM Scenarios at a Glance

Key Capabilities of MDM

Business Process Example: Successful Marketing Campaign

A correct address is of high importance, especially if the success of your company relies on error-free and smooth communication. If you can ensure that yourcustomer address data is correct prior to launching a marketing campaign, you can save a lot of money by avoiding double shipments and returns. Customers,who do not receive a shipment are dissatisfied, while customers who receive multiple shipments are annoyed. The quality of your marketing campaign has beennegatively affected.

SAP NetWeaver MDM gives you the capability to check the quality of the customer data before you start a marketing campaign. You can correct poor addressdata or identify duplicate customer records. In this way you reduce high shipment costs and increase customer satisfaction. The success of your marketingcampaign has improved.

Business Decision Example: Global Spend Analysis

In your company you have different locations with different business systems that are not synchronized. At each location you buy goods from the same vendor. Thefinancial reports do not reflect these expenditures. If you knew the total business volume for this vendor, you could negotiate better prices.

SAP NetWeaver MDM provides consolidated reporting of your expenditures. You transfer the vendor data from your business systems to a single MDM

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repository. Here you identify the vendors for which there are several master data records. For example, a vendor has the keys 825811, 67396, and 56113 indifferent business systems. SAP NetWeaver MDM informs you that these 3 keys belong to a single vendor. This is called key mapping. Key mapping enablesyou to create an accurate report by accumulating the expenditures related to the same vendor (for example in SAP NetWeaver Business Intelligence). With thisinformation you are able to negotiate better prices.

1.1.2 MDM Scenarios at a GlanceSAP NetWeaver MDM provides the following six core and business scenarios to help companies maintain their master data:

Master Data Consolidation - In this scenario, users wield SAP NetWeaver MDM to collect master data from several systems at a central location, detect andclean up duplicate and identical objects, and manage the local object keys for cross-system communication. With this consolidated data, users can access theinformation they need to perform company-wide analyses and consolidated reporting.

Master Data Harmonization - This scenario enhances the Master Data Consolidation scenario by forwarding the consolidated master data information to allconnected, remote systems, thus depositing unified, high-quality data in heterogeneous system landscapes. With this scenario, you can synchronize globallyrelevant data across your system landscape. For example, you can assign the same address to all occurrences of a particular customer.

Central Master Data Management - Whereas the emphasis in the Master Data Harmonization scenario is on local data maintenance, the Central Master DataManagement scenario focuses on creation and maintenance of data in the central data repository. It then distributes the newly created data to the connectedapplication systems where it can be complemented with locally relevant information.

Rich Product Content Management - This scenario is intended for the product information management (PIM) market, as it offers many functions for managingproduct data and corresponding image files centrally via SAP NetWeaver MDM. It can also be used to prepare for publishing product catalogs, either in electronicWeb format or in print.

Customer Data Integration - The Customer Data Integration scenario lets you harmonize customer master data records across heterogeneous systems.

Global Data Synchronization - Through the Global Data Synchronization industry scenario, reunified object information is synchronized with global data pools,such as 1Sync, in a standard industrial format, then provided to trading partners.

More information:

Scenarios

1.1.3 Functional ComponentsA complete MDM solution consists of inherent MDM components (shown in the blue background) and various other components.

The following figure illustrates these functional components:

The MDM architecture supporting the scenarios listed in the previous chapter can be described as follows:

A user-centric data access layer provides user interfaces to support end-to-end master data maintenance processes. Specific portal iViews enable task-oriented UIs for occasional users without the need for local installations. These generic iViews are highly configurable and provide workflow integration to theUniversal Worklist (UWL). In addition to these portal-based UIs, MDM features high-fidelity Microsoft Windows-based user interfaces to support specific keyuser activities (MDM Import Manager, MDM Data Manager, MDM Syndicator and MDM Publisher).The MDM Server is the central storage location of all repositories and contains functions such as the engines for searching, matching and validating.Repository schemas can be flexibly designed in a model-driven approach utilizing the meta-model of MDM. The MDM Server provides the latest in-memory technology to guarantee instant data access and fast search results.SAP NetWeaver MDM features the following integration portfolio including required SAP NetWeaver products to communicate with business applications(SAP or non-SAP):

The MDM Import Server and MDM Syndication Server support the automated loading and distribution of master data to and from the MDM Server inclose cooperation with SAP NetWeaver Process Integration.Technical monitoring of the MDM Server components using CCMS and ABAP APIs is supported by the SAP NetWeaver Application Server. Threetypes of APIs in combination with generic Web Services provide efficient access for developers embedding MDM into applications or buildingcomposite applications.To improve data quality in BI, MDM features integration content and direct connectivity with BI.Enterprise Search connectivity is provided to integrate MDM into company-wide searches.

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1.2 Key Capabilities of MDMMDM can be divided into various key capabilities and offers a comprehensive set of tools and functions for all these key capabilities.

Import and export mechanisms, services and predefined content ensure that master data can be integrated from a wide range of sources. All these functions aredescribed in the master data integration section.

Master data operations comprises all functions and tools that are required in operational business after data has been migrated. This includes role-based accessto the data, for example, or powerful and efficient search capabilities.

To be able to perform business processes efficiently and without errors, high quality data is essential. In the key area of master data quality, MDM offers functionsand tools to guarantee high standards of master data quality in your company.

1.2.1 Master Data IntegrationMaster Data Integration bundles the features applied to integrate MDM with other technology layers of SAP NetWeaver, the SAP Business Suite, and third-partyapplications. Specific areas include the inbound and outbound data transfer process and service-enabled access to MDM data. The key capabilities of masterdata integration are described below.

Use MDM remote system extractor to extract customizing data in the initial setup of your MDM system

You can use the generic extractor to retrieve customizing entries from SAP remote systems such as SAP Enterprise Resource Planning (ERP), SupplierRelationship Management (SRM) or Customer Relationship Management (CRM), and to send them as reference data to the MDM Server.

You need the reference data in MDM to provide all the lookup tables (for example the county table) needed to consolidate and distribute SAP master data objects.

The extractor can process any customizing data, such as check tables and domain fixed values. The generic extractor is independent of the type of the SAPremote system and master data object.

More information: Generic Extractor for Reference Data

Use MDM remote system extractor to automatically extract master data

After extraction of customizing data you can use the generic extractor to extract master data from major SAP applications (R/3, ERP, CRM, SRM, IS Retail). Themaster data, such as products and business partners, can then be imported to an MDM repository.

More information: Loading Master Data in the Scenario Process Guide

Use MDM import mechanisms to load master data from various sources

The MDM Import Manager is used to interactively define the import map that is later used by the MDM Import Server. With the MDM Import Manager theelements of the source schema are mapped to the tables and fields of the MDM repository (target structure). In this way, the user can quickly load new masterdata records into MDM using a graphical interface. The Import Manager is also available in a server version, which enables an automated import. The ImportServer can be used if data is loaded directly from any kind of remote system.

More information: MDM Import Manager Reference Guide

Use MDM business content to integrate data

MDM business content includes MDM repository structures, validation rules, predefined inbound and outbound mappings, XML schemas , matching strategies,SAP NetWeaver XI content, extractors for different SAP systems and portal content.

Currently SAP ships content for the following types of master data and SAP application systems:

Supported SAP Application Systems and Content

More information:

MDM content and XI content: Scenario Configuration GuidePortal content: Portal Content

Use MDM Syndicator to distribute master data to various targets

The MDM Syndicator is used to provide harmonized data to other applications as XML or in a variety of other formats. It is the export interface for master datastored in an repository.

A syndication can be executed either manually or automatically with the MDM Syndication Server. You must use MDM's port for automatic export. This placesthe executed syndication in a defined target directory that is used for communication with other systems.

More information: MDM Syndicator Reference Guide

Use MDM APIs and Web services to integrate data

In addition to MDM Import Manager or MDM Syndicator there are various options for processing the data directly with other applications such as the programminginterfaces (APIs).

The MDM APIs can for example be used to

Administrate MDM Servers and model repositoriesAccess and modify master dataExecute MDM matching and workflow capabilities

MDM offers a Web Services Generator which enables generation of typed CRUD (Create, Read, Update, Delete and Search) web services on top of an MDMrepository; these typed interfaces are specific to a repository schema and have the following benefits:

Master Data Type SAP Application

Material SAP ERP, SAP R/3

Customer SAP ERP, SAP R/3

Vendor SAP ERP, SAP R/3

Employee SAP ERP, SAP R/3

Business Partner SAP ERP, SAP R/3, SAP SRM, SAP CRM

Product SAP ERP, SAP R/3, SAP SRM, SAP CRM

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Simple to useNo development skills are neededMore business oriented due to semantic data descriptions which makes it easier to develop application programs and to maintain the consistency of datawhen it is updatedEasy Development of a Web Service (WS) clientCan be used by modeling tools such as SAP NetWeaver Visual ComposerCan be used by BPM tools, such as Guided Procedures and Galaxy

More information: Programming Interfaces

1.2.2 Master Data OperationsMaster data operations provide the processing layer that ensures the right people have the right tools to centrally model and manipulate master data. Therefore,this key capability comprises the relevant features involved in master data governance and processing. Specific topic areas include data modeling, role-baseddata access, search, workflow-enabled data creation/maintenance including structuring, and data publishing.

Data Modeling

An MDM repository can include a variety of table and data types, many of which go beyond traditional SQL DBMS capabilities. Additionally, MDM's taxonomyand attribute features let you smartly compartmentalize records and data to create the most efficient data model possible.

More information: MDM Console Reference Guide, see the following sections:

MDM Repository StructureDesigning an MDM Repository

Role-Based Data Access

MDM provides multiple ways to access master data, including Windows applications such as the MDM Data Manager, a library of configurable iViews,specialized portal pages, and APIs for custom development.

All access to master data is controlled by a role-based security scheme. MDM roles define which records, tables, fields, and operations are available to theconnected user. Roles can be mapped to MDM usernames, users in an LDAP directory, and SAP logins. Access restrictions are applied immediately uponsuccessful connection to a repository.

More information: MDM Console Reference Guide, see the section, MDM Repository Security.

Search

With MDM's powerful "drilldown" search capabilities, an entire repository can be easily searched and any item located in a matter of seconds. As you selectattributes or values to search for, MDM automatically:

Applies the search selections (no "search" button to click)Returns a list of matching recordsUpdates available search criteria to include only values remaining in the returned records.

MDM also includes free-form search options such as literal text, keyword, and expression-based searches.

More information: MDM Data Manager Reference Guide → Searching for Records

Workflow-enabled Data Creation/Maintenance

MDM contains a full suite of rich clients, such as the MDM Data Manager, from which you can create, edit, and structure the contents of an MDM repository. Toeffectively manage these and other master data operations, MDM includes a workflow feature that can ensure an organization's compliance processes are beingfollowed.

Workflows consist of a sequence of steps such as user tasks, validations, and approvals. By creating and implementing workflows for standard master dataoperations, you can:

Assign tasks to specific users or groups.Validate data against business rules.Require approval for changed/created records.

More information: MDM Data Manager Reference Guide → MDM Workflows

Data Publishing

Through MDM, you can create and manage catalogs containing the rich product data stored in an MDM repository. Key catalog management features include:

Product families which are independent of a repository's taxonomy.Separate storage of images, PDF files, and other data which apply to all records in a family.Easy and intuitive catalog layout and design toolsConnection to "live" repository dataWeb and print publishing capabilities

More Information: Rich Product-Content Management

1.2.3 Master Data QualityThe goal of master data management is to provide first-class master data for sustained cross-system data consistency. The master data quality function includes awhole array of features to ensure quality standards for master data in the following categories:

Accuracy - Does my data adhere to defined formats and standards?Validity - Does my data contain incorrect information?Completeness - Does my data contain all the necessary information?Consistency - Does my data contain contradicting or duplicate information?

SAP NetWeaver MDM offers a number of functions for ensuring and improving data quality. Some of the key capabilities are described below.

Use validations and assignments to check the accuracy and consistency of your master data

With SAP NetWeaver MDM, you can use validations to help ensure that your centrally stored master data is accurate and can be used by the connected remotesystems. You can define validation expressions to perform many kinds of specific quality tests. These expressions are Excel-like formulas that are evaluated byMDM and return a distinct value for each record. The expressions are used within MDM in validations, assignments and calculated fields.

The quality tests implement sophisticated business logic into your validation. Some examples of how such tests can be used:

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Make sure all required fields are filled inMake sure non-lookup fields that do not have pick lists to enforce data integrity have a legal value (for example: Price > 0)Compare the values of different fields to make sure the relative values are valid (for example, Price > Cost)

You can perform the validations manually, automatically on data entry or automatically as a step in an MDM workflow.

More information: MDM Data Manager Reference Guide → Validation Records

MDM assignments are MDM expressions, similar to validations, except that:

Instead of returning a Boolean value indicating success or failure, they can return a data value of any type.Instead of displaying the expression result for each record in a column in the Records pane, they can assign it to the value of the specified field that can beedited by the user.

This is a useful feature for data cleansing after an import step or for central master data management of records in the MDM repository. With assignments, thefields values of selected master data records can be defined using expressions. This allows you to set default values for fields, for example.

More information: MDM Data Manager Reference Guide → Assignments

Create more complete and meaningful master data using the MDM Enrichment Architecture

The MDM Enrichment Architecture is used for integrating third-party data enrichment providers with SAP NetWeaver MDM. A typical scenario for using externalenrichment services is to complete and correct imported master data before matching and merging the duplicates.

The enrichment services typically perform operations that can be defined based on the context of a single record. Examples are address standardization, datanormalization and lookups against a standard repository.

More information: MDM Enrichment Architecture

Create non-redundant and consistent master data using matching and merging capabilities

The matching and merging capabilities are used to detect and clean up duplicates and to manage the local object keys for cross-system communication. Withthis consolidated data, users can access the information they need to perform company-wide analyses and reporting.

The first step when matching records is to apply an optional normalization and transformation for each field of the record. The transformations basically replaceinformation in a field, for example to expand abbreviations. In the next step, you apply matching rules and bundle these rules into matching strategies. Accordingto a matching strategy, for example, MDM calculates scores for the probability that specific records are possible duplicates, as shown in the following figure.

A high matching score indicates that a record is likely to be a duplicate record.

You can then compare potential duplicates and merge any objects that are in fact duplicates into a new record. Merging typically involves interactive decisionmaking.

When multiple records are merged, redundant records are deleted from the MDM repository, but the information about the remote keys of the correspondingrecords in the remote system is not deleted. This is done in MDM with the key mapping function. Key mapping maintains the relationship between the key of anobject in the remote system (as shown in the following figure) and the corresponding master data object in MDM.

This allows you to harmonize records in connected remote systems by synchronizing local master data records with the consolidated MDM record.

More information: MDM Data Manager Reference Guide:

Matching ModeKey Mapping

1.3 Step-by-Step Example of Harmonizing Master Data

TaskIn the following three to four hour tutorial, you will be introduced step by step to the basic functions of MDM core components using a simplified business partnerharmonization example. You will get to know a selection of MDM's master data integration, operations, and quality capabilities.

You load new business partner records from an XML file in a prepared MDM repository. The sample repository already contains business partner records basedon a lean SAP Customer Relationship Management (CRM) data model. The new records you import simulate business partners extracted from a CRM system inXML format.

The import triggers a simple MDM workflow that matches the newly added records against themselves and the records already contained in the repository. Basedon the matching result you can identify duplicates and merge them to one clean record. You then syndicate the consolidated records to an XML file that can beprocessed by the CRM source system.

ObjectivesAt the end of this tutorial, you will be able to:

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Handle MDM repositories on a basic levelHandle MDM workflows on a basic levelImport master data records from XML filesMatch and merge records based on predefined strategiesExplain the key mapping concept of MDMSyndicate records to XML files

PrerequisitesInstalled applications and authorizations

MDM ServerMDM ConsoleMDM Data ManagerMDM Import ManagerMDM SyndicatorAdministrator access to MDM Server

More information: http://service.sap.com/installmdm71 → MDM Installation Guides

Sample business partner content

Repository archive fileMaster data XML files

You can download the files at http://service.sap.com/installmdm71 → Step-By-Step Tutorial → Download Sample Data.

NoteMake sure that the MDM applications and the sample content have the same release and support package level.

Background Knowledge

You have read Getting Started with MDM.

1.3.1 Preparing the Sample Data

UseBefore you start the business partner master data flow you store the sample data, that is the MDM repository and the import XML file, in the right place.

PrerequisitesYou installed and set up the MDM components and the database as described in the installation guide.Your MDM Server is up and running.You downloaded the tutorial sample data from the SAP Service Marketplace.

Procedure1. Unzip the MDM 7.1 Tutorial Sample Data.zip file.2. Copy the sample MDM repository archive (MDM71_Business_Partner_Tutorial.a2a) to the Archives folder, which you can find on the machine on which

you installed the MDM Server under the following path:<Local drive> →usr → sap →<MDM SAP System> →<MDS instance> →mdm → archives

3. Store the MDM71_Business_Partners_from_CRM.xml file anywhere on your local drive for later use.

1.3.2 Preparing the MDM Repository

UseThe MDM repository containing the master data for the tutorial is shipped in the MDM archive file format. To prepare the repository for use you need to unpack thearchive, connect to the new repository and load it to the MDM Server.

ProcedureIn the MDM Console unarchive the repository

1. In the Console Hierarchy pane open the context menu of your MDM Server.2. From the context menu, choose Unarchive Repository.3. Log onto the database server.4. Enter a name for the sample repository and select the archive (MDM71_Business_Partner_Tutorial) from the dropdown list.

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The unarchiving process may take a few minutes. When it is finished a message is output (ignore the report). The repository appears in the Repositories listwith status Disconnected.

NoteThe console hierarchy is <MDM Servers> → <repositories> → <tables> → <fields>. When you select a level in the Console Hierarchy pane, theupper right pane displays a list of objects on the next lower level, and details of the object in the lower right pane.

For example, if you select a server in the Console Hierarchy pane, a list of repositories running on this server is displayed in the upper right pane, anddetails of one of the repositories are displayed in the lower right pane. If you select a repository a list of tables is displayed and so on.

Connect to the repository

1. In the Console Hierarchy pane open the context menu of the unarchived repository.2. In the context menu choose Connect to Repository.3. Enter Admin as username and leave the password blank.

When you are connected to the repository it has the status Unloaded. You can now see the repository properties in the Repository Detail pane.

Load the repository to the MDM Server

In the context menu of the repository, choose Load Repository → Immediate.

The loading process may take a few minutes. You can watch the progress in the Status field. When the loading is finished the repository has the status LoadedRunning.

ResultThe sample repository for the tutorial is running on the MDM Server. Now it is ready for imports, data manipulations, syndications, and a lot of other operations.

1.3.3 Reviewing the Data Model and Administration Data

UseThe shipped repository already contains the business partner data model and sample records as well as the necessary administration data. Before you startworking with the repository, familiarize yourself with the prepared structures.

ProcedureIn the MDM Console familiarize yourself with the business partner data model

1. In the Console Hierarchy pane expand the repository node.2. Click through the tables and fields.

The data model consists of the Business Partner main table and several lookup tables that provide fixed values and special data for the fields of the main table(for example Regions and Business Partner Roles). It also contains tables for record attachments ( for example Text Blocks and Images) as well as auxiliary datamanagement equipment (for example Masks and Workflows).

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Familiarize yourself with the administration information of the repository

1. Expand the Admin node at the bottom of the repository node.2. Click through the tables and details.

The administration data covers user/role management, reporting/tracking, and information for integrating remote systems as data sources and targets (RemoteSystems, Ports, XML Schemas).

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1.3.4 Getting Familiar with the Business Partner Records

UseTo familiarize yourself with the handling of master data records and the actual business partners in the sample repository have a closer look at the record mode inthe MDM Data Manager.

PrerequisitesThe sample repository was loaded.

ProcedureStart the MDM Data Manager with the sample repository

1. Launch the MDM Data Manager.2. In the initial dialog choose the MDM Server and the sample repository.3. Enter the logon data of the repository (user name Admin; no password).

The MDM Data Manager starts in record mode where you can search and maintain the business partner records. You can switch between the modes of theMDM Data Manager in the header toolbar.

Get familiar with the sample business partner records and the search features

By default the MDM Data Manager displays all records contained in the repository in the Records pane (upper right). You can narrow down the selection bychoosing one ore more parameters in the Search Parameter pane (left). The lower right pane displays tabs containing details of the selected record and someutilities.

The status line at the bottom of the MDM Data Manager window displays the total number of records and the number of records found by the current searchparameters.

To reset all current search parameters, choose Search → Reset Search or in the header toolbar.

Example

1. In the Search Parameters pane under Category → Attributes select Country of Origin and under Values select Germany.The number of records visible in the Records pane was narrowed down from 21695 to 11 business partners.

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2. Choose Search → Reset Search or .All 21695 business partners are displayed again.

ResultYou have got a first impression of the sample master data records and the basic Data Manager functions. Do not close the MDM Data Manager during thefollowing import steps. You will perform the matching and merging steps for the imported records in the MDM Data Manager.

1.3.5 Importing New Business Partner Records

UseNow that you are familiar with the repository, you can start importing new records. To simulate a real world situation, import XML files were extracted from a realSAP CRM system.

You open the MDM Import Manager, review the prepared mapping of the source file to the destination repository and then start the actual import.

ProcedureStart the MDM Import Manager with the sample repository and the import XML file

1. Start the MDM Import Manager.2. In the initial dialog select the sample repository and enter the login data (user Admin, no password).3. In the next step select type XML Schema, remote system MDC CRM, XML schema SAP MDM Business Partner 5.5.5, and browse for the sample XML

file you have downloaded and stored on your local drive.

Review the mapping of fields and values

The MDM Import Manager opens providing a side-by-side view of the structure of the source XML file and the data model of the destination repository.

In the Source Hierarchy pane (upper left) you see the data structure of the incoming data, and in the Destination Hierarchy pane (upper right) you see thestructure of the business partner repository. The record details are listed on the Source Preview tab (lower pane).

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1. Choose File → Open or and select the map _MDMBusinessPartner.The predefined map file that maps the source to the destination data structure opens.

2. To see the field and value mappings, choose the Map Fields/Values tab.For example the source field PartnerTypeCode is mapped to the destination field Partner Type.

3. To see if keys of the new and the existing records match, choose the Match Records tab.You only perform import matching to avoid having records with the same keys in the repository. The actual matching (duplicate check) is performed later bythe workflow. In the sample data no keys match; the records are therefore newly created during import.

Start the import process

1. To check if the mapping is complete, switch to the Import Status tab.If there are no open action items (such as unmapped fields) the status is Ready to Import.

2. To start the prepared MDM workflow after import, choose Configuration → Options. In the Configuration Options dialog Import → Checkout/Workflow andselect Data Import from the dropdown menu. Choose OK.The simple Data Import workflow matches the imported records against the existing records and passes them for final review. You will learn more about theworkflow and the matching process in the following chapter.

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3. Start the import by choosing Execute Import icon (exclamation mark).The import process may take a few seconds. A message informs you about the progress of the import.

4. Close the MDM Import Manager.

ResultThe new records are imported into the sample repository, added to the existing records and matched by the workflow.

1.3.6 Identifying Duplicates

UseNew business partner records are added to the existing records and automatically matched against them. You examine the strategies underlying the matchingprocess and check the matching result to identify duplicate records.

ProcedureCheck the import and review the applied matching strategy

1. Switch back to the MDM Data Manager and choose View → Refresh.In the status line at the bottom of the window you see that there are now 21702 records. The import added seven new records to the 21695 contained.Before you check the result of the matching, you review the predefined matching strategies and rules that were applied by the automatic workflow step.

2. In the header toolbar change from Record Mode to Matching Mode and choose the Rules tab.Matching rules determine which fields the matching is based on and how important equal (or token equal) values in certain fields are. For example a tokenequal full address of business partners results in a high score (50), an equal first name in a low score (20).

3. Choose the Strategies tab.A strategy applies matching rules, summarizes their scores and defines the thresholds for a high or low matching class.

Check the matching result and identify duplicates

1. Choose the Workflows tab.On the Workflows tab in Matching Mode you see all the open workflows in a matching step. In our case in the Tasks pane you see the Data Import workflowthat was launched when the records were imported. The workflow matched the new records based on the MDM_ORGANIZATIONS strategy.

2. Select the workflow step.Now you see only the matched records and their matching results in the Records pane (upper right).

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3. Choose the Matches tab.When you now select a record in the Records pane, the potential duplicates, their matching score (by rule and the overall), and the matching class aredisplayed on the Matches tab.A High matching class indicates that the record is very likely a duplicate, while a Low matching class indicates that the record might be referring to thesame business partner. Records with matching class None have some overlapping values, but not enough overlapping values to be a potential match.

Based on this information and the record data, you decide if the records are identical.

ResultYou identified the duplicates and are ready to merge the duplicates to one clean record.

1.3.7 Merging Duplicates

UseYou merge the duplicate records to obtain a single record in your system that represents one real world business partner. As a result of merging the duplicatesdisappear but the key mapping information retains the information as to where the source records came from.

ProcedureMerge the duplicate records

1. In the Records pane select the record Company Panorama St. Mr. Buyer.2. On the Matches tab select the duplicates of this record in the [Include] column.

3. Switch to the Merge tab.The duplicates are displayed side by side. Fields with different values are highlighted in red. Fields that are empty in one record but filled in another arehighlighted in blue.

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4. If you are sure which record should be retained copy its values to the [Merged Record] column by right-clicking its column header and selecting Set All fromthe context menu.You can change any field of the merged record until you execute the actual merge. You can type in values or add one of the values of a duplicate to themerged record by double-clicking the relevant field of the duplicate.

5. To merge the duplicates right-click any field on the Merge tab and choose Merge Records from the context menu.6. Repeat the procedure for the record Company Becker Berlin Fr. Schulze and its duplicates.

The Records pane now only displays the merged records and the records without duplicates.

Check the results and review the key mapping

1. Switch to the Workflows tab.2. Right-click the Data Import workflow and choose Next Step → Final Review from the context menu.

3. Switch to Record Mode and choose the Workflows tab.The Workflows tab in Record Mode displays all the workflows that require attention. The workflow Data Import has reached the Final Review step.

4. Review the consolidated records in the Recordspane.

NoteTo display the record details in a vertical layout, switch to the Record Details tab.

5. To review the key mapping of the merged records right-click the record and choose Edit Key Mappings from the context menu.

The key mapping maintains the relationship between the identifier (or key) of an object in the remote system and the corresponding master data object inMDM. The business partner Company Panorama Studios Mr. Buyer, for example, is available in the remote system MDC CRM along with two duplicates.

6. Close the MDM Data Manager.

ResultYou have removed the duplicates of the imported business partner records in MDM and are ready to export (syndicate) the changed data back to the sourcesystem or another remote system.

1.3.8 Syndicating Business Partner Records

UseYou export the changes you made to the business partner data to the connected remote systems using the MDM Syndicator. In your case you export the changed

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records to an XML file that can be processed by a remote system.

The MDM Syndicator UI is similar to the MDM Data Manager window. You can select a set of records for syndication as follows:

Using the Search Parameters pane you can narrow down the set of records that is displayed in the Records pane.You can select records directly in the Records pane.You can use the Suppress Unchanged Records feature to let the MDM Syndicator automatically select the records.

In the tutorial you apply the third option, because you only want to syndicate the records you changed during the merge.

ProcedurePrepare and Execute the Syndication

1. Start the MDM Syndicator and log onto the tutorial repository.2. To open the prepared syndication map, choose File → Open.3. Select remote system MDC CRM and the map MDMBusinessPartner_1.

The syndication map is similar to the import map. It ensures that the resulting XML file has a format and data model that can be processed by the remotesystem. On the Item Mapping tab, you can review details of the mapping (for example Partner Number in the repository is mapped to PartnerNumber inthe destination XML file).

4. Switch to the Map Properties tab and select the Suppress Unchanged Records property in the Value column.

The Suppress Unchanged Records property tracks whether or not a record has changed since the last time it was syndicated to a particular remote systemand excludes the records that did not change from the syndication.

5. Start the syndication by choosing Execute Syndication icon (exclamation mark).Then define a destination for the result XML on your local drive. The syndication process may take a few minutes. When it is finished a message is output.

Check the Result

1. Open the result XML file with any XML editor or browser.2. Check the XML structure and content.

If you did not change any records other than those changed by the merge there should be 8 records in the XML file.

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ResultYou have finished the tutorial and gained a basic practical understanding of how the MDM core components and MDM content work. You can use the tutorialrepository as a playground and test tool while diving deeper into the MDM capabilities.

You can for example try to perform a manual matching of the records contained in the repository. There are still duplicates because in the tutorial you onlymatched the new records, but not the existing records against each other.

The tutorial repository offers additional useful content, such as sample validations, assignments, and ports, to practice with. Go and explore MDM.

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