The two use caseswebMethods OneData MDM has long supported both operational and analytical styles of Master Data Management. Though the two styles offer distinctly different advantages and use cases (and while operational MDM might precede the implementation of analytical MDM), the success of either style is dependent and benefited by very similar MDM functionality and system architecture.

The term operational (and its associated term, transactional), applies to the processing of business master data, such as customer names, vendors, products, services and locations (to name a few primary examples). In the course of doing business, operational master data (created and updated in ERP, CRM, vendor management systems, etc.), is sent daily (perhaps, even hourly) from business systems to the MDM hub where it is merged, cleansed, enriched, reconciled and subsequently synchronized back as gold-copy master data to the systems of origin. One might argue that the term process-driven MDM could be revised to Operational-Driven MDM given that Operational MDM’s larger mission is to improve business or operational processes by providing MDM’s “single-version-of-truth”.

But analytical MDM is actually Process-Driven, as well. While operational MDM enables improved process productivity and data quality, maximizing the daily routine of business systems, analytical MDM’s mission is to also provide a single version of truth which is consumed by business intelligence tools and data warehousing applications, thereby substantially improving the analytical processes that support critical decision making and compliance reporting, including the management and analyses of different subject area hierarchies.

To summarize, operational and analytical MDM readily coexist in the enterprise landscape, but for distinctly different purposes:

webMethods OneData: Operational/Analytical MDMOne MDM Product: Two MDM Styles

TABLE OF CONTENTS

1 The two use cases

2 How webMethods OneData MDM supports both operational & analytical MDM

4 Summary

CHARLES GREENBERG

Sr. Manager, MDM Product Marketing Software AG

BUSINESS WHITE PAPER

Source Enterprise Systems MDM Function Data Sets Areas of Benefit

Customer/Product/Location Data Systems (CRM, Billing, ERP, Financial Systems, etc.)

Synchronizing and reconcil-ing master data between two or more individual operational systems in support of ongoing/trans-actional processes

Customer, Supplier, Vendor, Employee, Product, Services, Assets, Locations, Ge-ographies, Financials

Improved customer ser-vice, order-to-cash (order entry, order fulfillment, order entry, distribu tion); synchronized sales and marketing activities; standardized creation/management for counter-party; process improve-ment

Operational MDM

Get There Faster 1

How webMethods OneData MDM supports both operational & analytical MDM

Data interchange / system interoperabilityIn order to support both the operational and analytical MDM use cases mentioned in the customer case study (left-hand margin), there was a fundamental requirement that the MDM tool flexibly connect with all the necessary counterparty sourcing applications and databases, as well as enterprise data management tools (including BI tools). OneData’s open and pluggable architecture (in addition to providing complete read/write database support), actually enabled integration to third-party data management tools, including the customer’s data modeler, data quality engine and ESB.

(It should be noted that in any OneData implementation, this level of integration and data interchange is available, out-of-the-box: Fig. 1)

Using multiple architectural stylesAgain citing the customer success story, the operational and analytical use cases also required the kind of interrelating of source system-to-hub versatility provided through OneData’s support for different MDM architectural styles (OneData supports five, see Fig2.) Since OneData is truly multi-domain in scope, and does not restrictively adhere to a single MDM architecture or process flow, the MDM solution could flexibly adapt to changing system, data management and reporting requirements.

Business White Paper | wM OneData: Operational/Analytical MDM

Source Enterprise Systems Function Data Sets Areas of Benefit

Customer/Product/Location Data Systems (CRM, Billing, ERP, Financial Systems, etc.)

Synchronizing and reconcil-ing master data between two or more individual operational systems in support of analytical processes

Revenue, Inventories, Credit Scores, Product Hierarchies, Chart of Accounts

Improved historical, pre-dictive analysis for areas such as demographic buying patterns, regional productivity and legal or regulatory compliance; financial analysis (liquid-ity, profit & profit margins, etc.); process improve-ment

Analytical MDM

Figure 1. OneData, out-of-the-box integration capabilities. (*signifies out-of-the-box adapters).

Customer Case StudyA Fortune 50 multinational conglom-erate selected OneData to support operational and analytical MDM use cases required by the company’s treasury function for creation of counterparties. In order to eliminate duplication, manual consolidation ef-forts and unsynchronized master data across disparate systems, OneData was implemented as the central-point of governance for counterparty creation and management, including underwriters and paying agents.

Additionally, OneData was deployed as the centralized platform providing trusted data to feed business intel-ligence reporting, risk exposure and legal compliance.

Get There Faster2

Initially, all operational and analytical data was consolidated into the OneData MDM hub, merged, cleansed and reconciled, producing one-single view of counterparty. Moving forward, the OneData hub (i.e., repository) added comprehensive deployment capabilities, enabling gold copy data to be synchronized (either in real-time or in scheduled batch-mode), back to originating downstream applications and databases. But the most utilized implementation mode was OneData’s centralized architectural style which enabled data stewards to create new counterparty records in the MDM hub through OneData’s rule-driven, workflow and enrichment processes.

Data governance functionalityRegardless of industry or data model, subject matter experts in the area of data management will find both operational and analytical use cases firmly supported through OneData’s highly configurable and rule driven, data governance paradigm.

Business White Paper | wM OneData: Operational/Analytical MDM

Successful MDM implementations often begin with selection of the architectural MDM style(s) that will best support the relationship between the MDM hub and enterprise systems.

Function Description

Import Exception Queue All excepted records queued for manual intervention that don’t automatically conform to rules of import.

Stewardship Controls / Data Security Role-based permission with granularly defined access.

Workflow Approval Process Multi-layered routings, triggered by type of data change and supported by proactive collaboration.

Hierarchy Management Modeling any parent/child relationship, and managed through the MDM paradigm, including versioning.

Get There Faster 3

Business White Paper | wM OneData: Operational/Analytical MDM

SummaryBecause the end result or outcome of operational and analytical MDM is so different, one is initially inclined to believe that both styles should be supported by two distinctly, different MDM technologies. But this perspective overlooks the essential collaborative nature of MDM. Indeed, OneData’s deep level of collaborative functionality enables data stewards, system administrators and business users internally to join as one team to manage compliance and implement prescribed data management rules that support data entry, data creation, data cleansing and enrichment, or data governance in general.

As discussed, data interchange/system operability represents a second level of high collaboration maintaining the relationship between webMethods OneData and all relevant external source and subscribing systems, databases and tools across the enterprise landscape.

This is just not key to successful operational and analytical implementations, but core to any MDM implementations—now, and into the foreseeable future.

Get There Faster

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