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ORACLE主数据管理技术方案
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2009-04-24
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论述了ORACLE主数据管理的解决思路、总体架构、应用功能等。
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Master Data Management
An Oracle White Paper
November 2007
Master Data Management
ii
Master Data Management
Introduction ....................................................................................................... 1
Overview ............................................................................................................ 1
Enterprise data...................................................................................................3
Transactional Data........................................................................................4
Operational MDM .................................................................................... 4
Analytical Data ..............................................................................................4
Analytical MDM........................................................................................5
Master Data ................................................................................................... 5
Enterprise MDM.......................................................................................5
Information Architecture .................................................................................5
Operational Applications............................................................................. 6
Enterprise Application Integration (EAI) .............................................6
Service Oriented Architecture (SOA) .................................................... 7
The Data Quality Problem.......................................................................7
Analytical Systems.........................................................................................8
Enterprise Data Warehousing (EDW) and Data Marts ...................... 8
Extraction, Transformation, and Loading (ETL).................................8
Business Intelligence (BI)......................................................................... 9
The Data Quality Problem.......................................................................9
Ideal Information Architecture.................................................................10
Oracle Fusion Architecture .......................................................................11
Master Data Management Processes............................................................12
Profile ...........................................................................................................12
Consolidate ..................................................................................................13
Govern .........................................................................................................13
Share .............................................................................................................14
Leverage .......................................................................................................14
Oracle MDM High Level Architecture........................................................14
Oracle Fusion Middleware ........................................................................15
Application Integration Services...........................................................15
Business Process Orchestration Services.............................................16
Data Quality & Standardization Services.............................................16
Data Integration & Metadata Management.........................................16
Business Rules Engine............................................................................17
Business Event Services .........................................................................18
Identity Management..............................................................................19
Web Services Management....................................................................19
Analytic Services......................................................................................19
Enterprise Performance Management............................................19
Data Warehousing .............................................................................19
Business Intelligence .........................................................................20
Publishing Services ............................................................................20
Master Data Management
iii
Additional FMW Services ......................................................................20
Application Development Environment .......................................20
High Availability, Scalability & Mixed Workload Support..........24
Application Integration Architecture.......................................................24
AIA Layers ...............................................................................................24
Common Object Methodology.............................................................24
MDM Applications .........................................................................................22
MDM Pillars ................................................................................................22
Customer Hub .................................................................................................22
Customer Lifecycle Management Process ..............................................22
Customer Profile Lineage with Point in Time Recovery ......................22
Centralized Information Quality Management ......................................23
Comprehensive Data Model .....................................................................23
Modularity and Flexibility..........................................................................23
Policy Management ....................................................................................23
Product MDM Data Hub...............................................................................24
Import Workbench.....................................................................................25
Catalog Administration ..............................................................................25
New Product Introduction........................................................................26
Product Data Synchronization..................................................................26
Hyperion Financial Hubs and Data Relationship Management...............27
Automated Attribute Management ..........................................................28
Best-of-Breed Hierarchy Management ....................................................28
Integration with Operational and Workflow Systems...........................28
Import, Blend, and Export to Synchronize Master Data .....................29
Versioning and Modeling Capabilities to Improve Analysis ................29
MDM Implementations..................................................................................29
Build vs Buy.................................................................................................30
Oracle Implementation Services...............................................................30
Conclusion........................................................................................................31
Master Data Management
INTRODUCTION
Fragmented inconsistent Product data slows time-to-market, creates supply chain
inefficiencies, results in weaker than expected market penetration, and drives up
the cost of compliance. Fragmented inconsistent Customer data hides revenue
recognition, introduces risk, creates sales inefficiencies, and results in misguided
marketing campaigns and lost customer loyalty
1
. “Product” and “Customer” are
only two of a large number of key business entities we refer to as Master Data.
Application fragmentation negatively impacts an organization’s ability to maintain
proper governance processes, mitigate risk, and provide accurate timely
compliance reports.
Master Data is the critical business information supporting the transactional and
analytical operations of the enterprise. Master Data Management (MDM) is a
combination of applications and technologies that consolidates, cleans, and
augments this corporate master data, and synchronizes it with all applications,
business processes, and analytical tools. This results in significant improvements in
operational efficiency, reporting, and fact based decision-making.
Over the last several decades, IT landscapes have grown into complex arrays of
different systems, applications, and technologies. This fragmented environment
has created significant data problems. These data problems are breaking business
processes; impeding Customer Relationship Management (CRM), Enterprise
Resource Planning (ERP), and Supply Chain Management (SCM) initiatives;
corrupting analytics; and costing corporations billions of dollars a year. MDM
attacks the enterprise data quality problem at its source on the operational side of
the business. This is done in a coordinated fashion with the data warehousing /
analytical side of the business. This combined approach is proving itself to be very
successful in leading companies around the world.
This paper will discuss what it means to ‘manage’ master data and outlines Oracle’s
MDM solution. Oracle’s technology components are ideal for building master data
management systems, and Oracle’s pre-built MDM solutions for key master data
objects such as Product and Customer can bring real business value in a fraction of
the time it takes to build from scratch. Oracle’s fusion of applications and
technology creates a solution superior to other MDM offerings on the market.
OVERVIEW
How do you get from a thousand points of data entry to a single view of the
business? This is the challenge that has faced companies for many years. Service
Oriented Architecture (SOA) is helping to automate business processes across
disparate applications, but the data fragmentation remains. Modern business
analytics on top of terabyte sized data warehouses are producing ever more
1
Customer Data Integration – Reaching a Single Version of the Truth, Jill Dyche, Evan Levy Wiley & Sons,
2006
“Through 2010, 70 percent of Fortune 1000
organizations will apply MDM programs to
ensure the accuracy and integrity of commonly
shared business information for compliance,
operational efficiency and competitive
differentiation purposes (0.7 probability).”
Gartner, Jan. 2006
Master Data Management
2
relevant and actionable information for decision makers, but the data sources
remain fragmented and inconsistent. These data quality problems continue to
impact operational efficiency and reporting accuracy. Master Data Management is
the key. It fixes the data quality problem on the operational side of the business
and augments and operationalizes the data warehouse on the analytical side of the
business. In this paper, we will explore the central role of MDM as part of a
complete information management solution.
Master Data Management has two architectural components:
• The technology to profile, consolidate and synchronize the master data
across the enterprise
• The applications to manage, cleanse, and enrich the structured and
unstructured master data
MDM must seamlessly integrate with modern Service Oriented Architectures in
order to manage the master data across the many systems that are responsible for
data entry, and bring the clean corporate master data to the applications and
processes that run the business.
MDM becomes the central source for accurate fully cross-referenced real time
master data. It must seamlessly integrate with data warehouses and the Business
Intelligence (BI) systems, designed to bring the right information in the right form
to the right person at the right time.
In addition to supporting and augmenting SOA and BI systems, the MDM
application must support data governance. MDM enables orchestrated data
stewardship across the enterprise.
In order to successfully manage the master data, support corporate governance,
and augment SOA and BI systems, the MDM applications must have the following
characteristics:
• A flexible, extensible and open data model to hold the master data and all
needed attributes (both structured and unstructured). In addition, the data
model must be application neutral, yet support OLTP workloads and
directly connected applications.
• A metadata management capability for items such as business entity
matrixed relationships and hierarchies.
• A source system management capability to fully cross-reference business
objects and to satisfy seemingly conflicting data ownership requirements.
• A data quality function that can find and eliminate duplicate data while
insuring correct data attribute survivorship.
• A data quality interface to assist with preventing new errors from entering
the system even when data entry is outside the MDM application itself.
• A continuing data cleansing function to keep the data up to date.
• An internal triggering mechanism to create and deploy change
information to all connected systems.
剩余37页未读,继续阅读
资源评论
- wyt12132012-08-24不错哦,架构的部分,讲的还是比较清晰了,可惜就是有点太概要了
- shouqe12014-03-14可以参考,值得学习,已经应用到我的系统中
- ghoast_li2012-11-02很清楚,格式也很好,赞
- chenghaoren12342013-10-28不错,思路清晰,容易理解
leitw1
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