Book Image

Microsoft SQL Server 2008 R2 Master Data Services

Book Image

Microsoft SQL Server 2008 R2 Master Data Services

Overview of this book

Table of Contents (18 chapters)
Microsoft SQL Server 2008 R2 Master Data Services
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Master data


Before we start managing anything, we need to define what master data actually is. Master data can quite simply be thought of as electronic data that represents any noun belonging or related to the business.

Examples of these nouns are:

  • Products

  • Customers/clients

  • Projects

  • Employees

  • Properties

  • Accounts

  • Suppliers

  • Vendors

  • Stores

Looking at the aforementioned list, we're clearly not mentioning sales data, or inventory data, for example. Instead, master data is the non-transactional data that gives the transactional data some context. For example, our sales system records a transactional sales amount, but this sale is given context by the Product and Customer.

A subject area of master data, such as Customer or Product, is known as an entity. If we take Product as an example, we can derive a number of characteristics about the product, which are known as attributes of the entity. When we think of any average product, such as an item of clothing, that product will typically have a color, a size, a brand, and so on.

In fact, a product may actually have more attributes than you may think. A more complete picture of what a product entity and its attributes might look like is shown next:

The entity and its attributes define a clear and robust structure for our Product master data subject area. However, a structure is nothing without data itself. The data in the case of the Product entity comes from a collection of members, which can be thought of as the physical instances of a given entity.

Each member of the entity will be different from every other member in some sort of way. This is usually achieved through the use of a code or unique identifier (such as the Product's SKU—which stands for Stock Keeping Unit—a unique identifier for items that are for sale in a retail store or other business), but it could easily be from a combination of attributes. An example of the different members for the Product entity is as follows:

SKU

Description

Category

Sub Category

Color

J10001

Men's Regular Fit Jeans

Clothes

Jeans

Blue

J10002

Men's Loose Fit Jeans

Clothes

Jeans

Blue

J10003

Men's Loose Fit Jeans

Clothes

Jeans

Black

The above concepts of entities and attributes are very similar to dimensions, attributes, and members in dimensional data warehouse design and Online Analytical Processing (OLAP) systems, for readers familiar with these concepts.