Master data is a distinct class of data that must be managed well for data sharing, or exchange, to be successful within an enterprise. Failure to do so leads to well-known data quality problems that may severely limit data warehouses and linked transaction systems. This is because master data has its own unique properties and behaviors that require specific management techniques to be applied to it. General data management approaches are simply insufficient. This tutorial explains how to manage master data with the goal of making it an enterprise-wide data resource. Specific issues in master data management (MDM) are described along with techniques to solve them. Particular attention is paid to the metadata required to manage master data, the relationship between master data and data quality, and the strong link between data governance and master data. MDM is dealt with from the strategic level, e.g. building a business case, down to the technical level, e.g. data models that extend master data to include management metadata.
Participants will learn about:
- The structure of master data, what sets it apart from other classes of data, and planning for its management.
- Organizational requirements for successful MDM, including stewardship and governance.
- Data architecture for master data, both at the enterprise level and the database design level
- Metadata and repository functionality required to carry out common MDM tasks.
- Current vendor approaches to providing solutions for MDM, and how to evaluate them.
This session will begin by comparing and contrasting data governance and master data management and end with a demonstration of how applying data governance principles and standards, enables attaining the goals of master data management. This will be accomplished through a comparison of two case studies, whereby the companies have actively engaged in data governance and master data management initiatives for over 3 years.
Nordea, the largest bank in Scandinavia has for several
years focused on Master Data Management. After several mergers information
quality and consistency are major challenges. One of the most challenging
areas has been to establish the right implementation strategy on Customer
Master Data. The strategy must on one hand contribute to the high demands
coming from the markets and customers; on the other hand it must contribute
to the high demands coming from within the company. To top this off, the
progress will be very dependent on the organizational maturity which is
always one step behind.
This session will share with you:
- The approach behind the strategy
- The experiences from putting that approach into practice
- Key learning points from Nordea
If you asked a business person "What is MDM?"
The answer might be: Medical Decision Making, Manufacturing Distribution
& Marketing or Multi Dimensional Media. All of these are valuable and
accurate in their own space but we as data professionals need the business
knowledge and acumen that is associated with Master DATA Management and
Metadata Management. Gathering this knowledge, sustaining it and making
it available across the organization is what Master Data Management is
all about.
An MDM architecture can be examined across three aspects:
Master Data Knowledge
-
Identifying that which is core "Master"
data to your company
- Understanding corporate business data – what are the bits and bytes
- Validating true business value ROI
- Define and providing
Governance and Stewardship
Master Data Content
- The metadata (library, dictionary, repository)
- Developing the rules to transform data
- Strategies for determining what the data is, who owns it etc.
- Developing a data model to show relationships between data
Master Data Maintenance
- Defining what
IT functions, infrastructure and data are needed to support Master Data
- Defining valid metrics
- Defining rules for valid values
- Providing a road map of steps to successfully execute a Master Data Management strategy
and maintain it.
This presentation is an opportunity to share what I have
gleaned as we strive to incorporate a Master Data Management strategy
in our ever evolving Information Portfolio.
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