Title: Integrated Master Data Management a focus on the total Business

The Master Data Management and Data Governance offerings are a designed for integration that leverages IBM’s best of class design for purpose components and

appliances.

This document can be found on the web, www.ibm.com/support/techdocs

Under the category of “White Papers.

Draft

Version Date: 2011

Systems GroupChuck Gray

grayc@us.ibm.comInformation Management Foundation Architect

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The business environment of today is demanding validation and control. This means the integration need has never been higher or with more demand. This requires ETL/ELT systems to blend data flows(both operational and analytic) with master data management. This is linked to data governance and integrated with in-flight data, at rest data (history and log). It is then incorporated with business application enabled by technology for appropriate service level driven by the SOA/ESB infrastructure stacks. This will drive the ability to build information trust and quality of information. A business is always working in questioning mode about is my business direction giving me everything that it should. The total business integration model is the only way to get a hold on trusted answers. This requires Master Data Management and Data governance offerings be designed for integration that leverages best of class design for purpose components and appliances. This includes operational and analytics support stacks and systems.

The process of Achieving data integration is not only a product, but also the integration of that product into the fabric of operational systems and analytical data hubs. It is applied to machine generated data, data in-flight while filtering data into analytic operations. It will leverage enterprise service business and Service Orient Architectures to reduce time to deploy models to help the business be more agile.

The processes used to achieve data integration between disparate systems that can improve business processes, enhancing total business performance, and make intelligent decisions. As part of integrated Information Management, master data management can help increase data consistency throughout the enterprise to create new business values and strategic advantage. In addition, you will benefit from a complete, sophisticated view of the customer, which will improve customer satisfaction and help place your company ahead of the competition.

Let us look at Applying the methods, techniques, and technologies that address data architecture, movement, storage, integration, and governance of enterprise information and master data.

Integrated Information Management Architecture for operational & analytical data hubs provide the foundation for leveraging information as a strategic asset. Information Management Architecture is a component-based, scalable, conceptual architecture where each layer is described in terms of people, processes, and technology.

The architecture establishes a framework, which guides the implementation of business solutions. This capability serves as the basis for evaluating the technical environment, determining the goal architecture, and developing the plan to achieve these objectives. Analytical data hubs provide centralized repositories of critical business information used for analysis and reporting. Analytical data hubs addresses repositories such as an Enterprise Analytical data hubs, focused warehouse, Operational Data Stores, data marts, and line-of-business (LOB) data repositories. The success of analytics enabled business is dependent upon

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having a flexible and extensible integrated Information Management Architecture and analytical data hub environment that can be used by subsequent business Intelligence and business analytical tools from operational and analytics environments.

Value Proposition:

It consolidates the various data silos / systems and provides access through the enterprise data hubs.

It establishes a flexible information platform and provides the foundation for achieving business analytical capabilities.

It helps ensure that the architecture is robust and flexible enough to support both immediate and long-term needs.

It provides efficiencies and reduces costs required to maintain the information infrastructure.

Integrated Master Data Management is defined as the set of disciplines, technologies, and solutions used to create and maintain consistent, complete, contextual and accurate business data for stakeholders (users, applications, data hubs, processes, companies, trading partners, customers) for access across and beyond the enterprise. It provides the facts describing your core business entities: customers, suppliers, products, and employees. Master Data Management decouples master information from individual applications while integrating business systems, and becomes a central application-independent resource. It simplifies ongoing integration tasks and new development by ensuring consistent, accurate master information across transactional and analytical systems. It helps clients gain a single view of their domains and proactively address data issues.

It provides consistency, simplification and uniformity of process, analysis and communication across the enterprise.

It eliminates the need for separate departmentally maintained versions of the truth. It allows for a workflow-driven process in which business units and IT collaborate to

harmonize, cleanse, publish and protect common information. It eliminates time-consuming debates about data accuracy and data definitions and

facilitates improved decision making.

Data Modeling & Business Models define the attributes, context, relationships, and structure of the information that will be available for analytical processes. A data model is a detailed logical representation of the data for an organization or for a business area. It is used as a tool between a data modeler and business user to communicate abstract business data concepts, and provide feedback required to affirm the model. In developing next-generation business

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operational and analytical solutions, a data model is critical to ensure that the solution can answer the questions posed by the business users. Industry Models are a related area that combines deep subject matter expertise and industry best practice in a usable form that can be leveraged by both business and information technology communities. Industry Models accelerate solution development by providing pre-built structures that cover a wide range of industry-based data needs.

It provides a clear understanding of the attributes and relationships that exist within data environments.

Leverages pre-existing industry-specific data models to accelerate solution development.

It facilitates successful business engagements with a baseline for reporting and subsequent analytical processes.

Maintain focus on data models that address challenges of the business.

Adding to the core integration of Information Management and Master Data Management is Information Governance. Information Governance is the orchestration of people, process, and technology to enable an organization to leverage data as an enterprise asset. The core objectives of an information governance program are to ensure that the information being governed is consistently defined and well understood, increase the use and trust of enterprise data, and guide data management-related decision-making. Like rules of debate, information governance provides a common language that makes it possible to understand and act on information across functions and lines of business. When meaning is unclear, analysis is flawed and business objectives suffer. Strong information governance discipline can help organizations move faster and collaborate more easily both within the enterprise and with partners.

It enables the execution of an organization's business goals and develops information as a corporate asset.

It facilitates revenue growth through consistent, comparable and quality data required to improve decision making.

It provides a data infrastructure that meets regulatory requirements and can respond to future changes and expectations.

Impact's customer loyalty through improved understanding of a customer's data across business lines for targeted sales and service

 

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Appendix A: Example of areas of value

Integrated Master Data Management helps in semantic consistency of master data between financial and non-financial data (operational and analytic hub data)

Although financial consolidation systems enable a top-down analysis of financial and non financial data, they don't support any analysis across transactional systems at the source level (for example, a view of orders by the customer across multiple sales order management systems). Financial consolidation systems effectively create a separate silo of aggregated financial and management data.

1) Integrated Master Data Management can help address this disconnect. First, Integrated Master Data Management would enable the sharing of master data across multiple systems for operational and analytical use cases. If the finance users defined an aggregation hierarchy to consolidate data by regions, business units, and companies in the financial consolidation system, then this hierarchy could also be used to analyze data from transactional systems. This would, ensure that roll ups used in reporting sales data were consistent with those used in reporting financial data.

2) Integrated Master Data Management would help close the loop between financial and non-financial data. It can help ensure that operational master data, is consistent. This also helps ensure that data is aggregated in the financial consolidation system using the same fundamental data elements that exist in the transactional systems. This enables better drill down from aggregated financial data to the underlying operational systems. The key value is the shared and unified governance routine that Master Data Management creates across the enterprise.

Integrated Master Data Management ensures Consistency and enables flexibility. Organizations use standardized master data to support consistency, simplification, and uniformity of process, analysis, and communication across the enterprise. When the master data is implemented it moves the organization closer to long-sought objectives of data sharing within the larger application portfolio.

Enterprises can then help break down operational silos. A sound and integrated master data program helps organizations break down operational barriers, enabling greater enterprise flexibility and simplifying system integration activities.

Integrated Master Data Management is a workflow-driven process in which business units and IT collaborate to harmonize, cleanse, publish, and protect common information assets that must be shared across the enterprise. Master Data Management ensures the consistency, accuracy, stewardship and accountability for the core information of the enterprise.

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Organizations apply Integrated Master Data Management to eliminate endless, time-consuming debates about "whose data is right" and "whose definition of sales will be used today," which can lead to poor decision making.

To support Integrated Master data management standardization a blending of a solid Service Oriented Architecture (SOA) model must be developed along with a business strategy of master data management. This is very important to the success of business as it moves to the next generation competitive business paradigm. In developing this solid business strategy enabling master data management standardization with defined priorities and service oriented architecture (SOA) this will enable alignment of master data, reference data, and metadata.

A host of data quality issues indirectly or directly arising out of the lack of data standardization in the business Information Life Cycle. Leveraging Service Oriented Architecture for Data Consistency and master data management standardization is the Key to Quality Data while enhancing functions like data standardization, cleansing, and formatting to promote consistency in data capture and reporting an increase the effectiveness of data matching processes used to deliver uniqueness, verification, and enrichment capabilities for the business and decision process.

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Appendix B: Information intelligence can make the difference.

Use of Information management (Intregrated Master Data Management) at State of Washington: (This is a painful memory for us that watch it unfold, but show how we could have potentially discovered and maybe stop this horrible loss.)

The State of WA – Administrative of the Courts (AOC) operates under the supervision of the Chief Justice of the Supreme Court. The Information Services Division (ISD) of the AOC, provides support to the courts through the development, operation, and maintenance of the Judicial Information Systems (JIS) that supports automation in juvenile, municipal, district, superior and appellate courts for over 10,000 users.

TRAGEDY Occurred in November 2009: Maurice Clemmons, a five time convicted felon had been arrested and jailed on numerous occasions, including assault of a police officer and raping a child. He was released on bail by a WA State Judge who did not have the facts to assess his risk and Maurice Clemmons, one-week later- murdered four State of WA police officers.

AOC CHALLENGES:

1.) Inability for the judges to understand the suspect in their courtroom with info for a risk assessment to make informed sentencing decisions resulting from improved public safety.

2.) Duplicity in the AOC Criminal Defendant database that contains over 7 million records, even though the State of WA only has a population of 6.5 million people

3.) Better understand suspects, or false negatives, in which a person is entered multiple times in the system and don’t link to other records, therefore the Judge would not be able to assess the risk and make informed decisions on sentences.

AOC RESULTS:

1.) POC analysis in one week with 3 million defendant records - found over 120,000 false positives and over 160,000 false negatives.

2.) AOC Judges now have access to real time criminal data from their own AOC historical database, additional adult incarceration data from the Department of Corrections, Criminal Historical Data for Out of State Offenders from the State Patrol, incarceration data from the Juvenile Courts and also fraudulent data from Department of Health and Social Services Dept. for a comprehensive risk assessment to provide appropriate sentences and improve public safety for citizens & police.

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