Bøger af Andy Graham

Master Data Management (MDM for short) has become a whole industry, within an industry. There are many companies now claiming to be MDM software (or services) providers. Everyone wants a master data project on their CV, and in general it has become hip and trendy to talk about and do. The reality is that MDM is in fact the reincarnation of the problem of how to manage the consistency and integrity of the myriads of data assets that exist across the enterprise. This book provides an understanding of MDM, the business drivers behind it, the various techniques that are critical to its success and gives a good architectural grounding in the subject. It is perfect for anyone embarking on an 'adventure' in this problem space. The intended audience of this text include data professionals, managers of data professionals, project/program managers, IT architects of all kinds and business analysts. There are also a number of chapters, specifically chapters 1, 3, 5 and 13, which will be of interest to the executive levels within an organisation. This book covers a range of subjects within the master data management world. There are 13 chapters: - Chapter 1 - Here be Monsters: The book starts with a general overview of the reason why master data management is important and the history of where it has come from. - Chapter 2 - What is Master Data: We next look at what is master data and how to spot it within your organisation. - Chapter 3 - The Business Case for MDM: This chapter looks at the business drivers and some of the fundamentals that comprise the MDM business case. In effect this is the show me the money chapter. - Chapter 4 - Architecture, Principles and Concepts: This chapter is an architectural breakdown of what constitutes an MDM system. It provides us with a basic reference architecture with which to explore the MDM world. - Chapter 5 - Master Data is Risky: master data has inherent risks associated with it. This chapter looks at what those are and some of the approaches to mitigation. - Chapter 6 - Magnum Opus: One of the key achievements for the MDM architect is the creation of the gold record. Behind this concept is the identification of the data sources that make it up. This chapter gives us a good grounding in the concept. - Chapter 7 - It's a Huge Job: This chapter looks at how we find all the master data and keep this information up to date, without having to employ the world. - Chapter 8 - The Hub: The master data hub is an important concept to understand and is in fact central to most MDM technologies. This chapter takes a look at this idea. - Chapter 9 - The Cross Walk: This chapter looks at the challenges faced when using different reference systems and how to address them. - Chapter 10 - Identity Management: With this chapter we examine some of the practicalities of identifies and how to manage them. - Chapter 11 - Record Linkage: How do we bring data together from different systems and create a single harmonised record. This chapter addresses this difficult problem by looking at the techniques and processes involved. - Chapter 12 - The Challenges of Global MDM: We live in a global world and therefore our approach to MDM needs to be mindful of this and handle the nuances of different parts of the globe. - Chapter 13 - Project Challenges: The final chapter looks at the challenges associated with successfully instigating a MDM initiative.

Wouldn't it be great to understand all the data in your organisation? Just imagine being able to define, agree and manage information concepts that impact on business strategy? Then image that these information concepts can be linked to the physical database attributes that ultimately are used to create them. That's what this book is about. It focuses on the data model as the foundation for achieving this understanding. This book provides a framework for the enterprise data model, the business reasons behind it and the differences between conceptual, logical and physical data models. The question of how, and why, to use a data model artifact as part of the data governance toolkit for the whole enterprise is also addressed. This publication is not an in-depth manual on how to model data for a new database system or your next design project. It instead focuses at a level above these implementation projects and addresses the issues that organisations typical struggling with such as: * How do we provide a framework within which we can manage our data assets? * How do we develop applications that adhere to a set of data standards; without creating a nightmare of administration and governance that is both unwieldy and unusable? * How can we get business value from our enterprise data? Chapter headings are: * Chapter 1 - Introduction * Chapter 2 - Information and Data * Chapter 3 - Pillars of Value * Chapter 4 - An Overview of Data Modelling * Chapter 5 - Data Architecture * Chapter 6 - The Enterprise Data Model * Chapter 7 - Build the Model one Project at a Time * Chapter 8 - Master Data * Chapter 9 - Data Governance * Chapter 10 - The Enterprise Data Framework This 2nd edition revises the original text to add extra details around key areas such as the enterprise data model framework and the pillars of value. It also improves the quality of the original text.