Introduction

This book describes how to build a successful business intelligence system and its underlying data warehouse databases using the Microsoft SQL Server 2005 product set. The key word here is successful.

The Data Warehouse and Business Intelligence System

Data warehousing and business intelligence are fundamentally about providing business people with the information and tools they need to make both operational and strategic business decisions. Well break this down a bit so you can really understand the nature and magnitude of what youre about to take on.

First, your customers are the business people in the organization. But not all business people carry the same importance to youyoure especially concerned with those who make strategic business decisions. Why? Because this is where the big money is. One well-made business decision can translate to millions of dollars in many organizations. Your main customers are executives, managers, and analysts throughout the organization. Therefore, the data warehouse and business intelligence (DW/BI) system is high impact and high profile.

Strategic also means important. These are decisions that can make or break the organization. Therefore, the DW/BI system is a high-risk endeavor. When strategic decisions are made, someone often wins or loses. Therefore the DW/BI system is a highly political effort.

Increasingly, the DW/BI system supports operational decisions, especially where the decision maker needs to see historical data or integrated data from multiple sources. Many analytic applications have this operational focus. Whether the decision making is strategic or operational, from a technical perspective, you need to provide the information necessary to make decisions. Any given decision will likely require a unique subset of information. Youll need to build an information infrastructure that pulls data from across the organization, and potentially from outside the organization, and then cleans, aligns, and restructures the data to make it as flexible and usable as possible. Whereas most transaction system modules work with one type of information, such as billings, orders, or accounts receivable, the DW/BI system must eventually integrate them all. Therefore, the DW/BI system requires technically sophisticated data gathering and management.

Finally, you need to provide the business decision makers with the tools they need to make use of the data. In this context, tools means much more than just software. It means everything the business users need to understand what information is available, find the subsets they need, and structure the data to illuminate the underlying business dynamics. Therefore, tools means training, documentation, and support, along with ad hoc query tools, reports , and analytic applications.

Lets review. The DW/BI system:

  • Is high profile and high impact

  • Is high risk

  • Is highly political

  • Requires technically sophisticated and complex data gathering and management

  • Requires intensive user access, training, and support

Creating and managing the DW/BI system is an extremely challenging task. We want you to take on this task with full knowledge of what youre getting into. In our experience, its easier to deal with all of the challenges if youre at least somewhat forewarned.

We dont mean this to discourage you, but rather to warn you before you jump in that the waters are swift and deep. In our experience, all the reasons that make the data warehouse challenging are also what make it a fun and exciting project.

The Kimball Group

While its true that building and managing a successful DW/BI system is a challenge, its also true that there are ways to approach it that will increase your likelihood of success. Thats what the Kimball Group is all about. Weve been working in the DW/BI area for more than 20 years . The authors of this book, who are members of the Kimball Group, have spent their careers working on data warehousing and business intelligence systems as vendors , consultants , implementers and users. Our motto is Practical techniquesproven results. We share a common drive to figure out the best way to build and manage a successful DW/BI system. We are also teachers at heart, with a strong desire to help you succeed and avoid the mistakes we and others have made.

Why We Wrote This Book

Data warehousing and business intelligence have been around in much the same form since at least the 1970s, and continue to enjoy an incredibly long technology lifecycle. In 1995, when the primary authors formed our first consulting organization, one of us voiced the opinion that data warehousing was finished, that the wave had crested and wed be lucky to get a few more projects before we had to go find real jobs again. Twelve years later, data warehousing and business intelligence are still going strong. In fact, its been only in the last few years that weve seen signs of maturation in the industry.

One of the signs of a mature market is the emergence of single-source providersa safe choice for risk-averse organizations. The data warehousing technology stack covers everything from esoteric source system knowledge to user interface design and best-practice BI applications. While many of the vendors scrambled to position themselves as end-to-end providers in recent years, it was clear to us that the database vendors are the only ones who can truly provide end-to-end solutions. In 2001, when we first discussed this book, we felt Microsoft was going to force the concept of a viable , single-source data warehouse system provider into reality, and at an attractive price.

Our belief in the move toward single-source providers means we must extend the Kimball Method techniques to the product-specific level, making them directly available to the market that will respond to the single-source provider. We chose the Microsoft toolset as our test case for two main reasons. First, the SQL Server 2005 is a strong BI platform. Microsoft has been investing heavily in extending and enhancing its business intelligence capabilities since the mid-1990s, when it invested in what has become the Analysis Services engine. The level of investment has since ramped up dramatically. With the start of development for SQL Server 2005, the SQL Server BI development team grew to over 200 people. Microsoft seems serious about bringing business intelligence to the mainstream market. Second, the two authors both worked at Microsoft from 1997 to 2002 or 2004. In particular, Joy was the manager of the SQL Server BI Best Practices group within the SQL Server Business Intelligence development team. This gave us a set of strong working relationships and access to key support resources. Who could pass that up?

Who Should Read This Book

This book covers the entire data warehouse lifecycle. As a result, it offers useful guidance to every member of the data warehouse team, from the project manager to the business analyst, data modeler, ETL developer, DBA, analytic application developer, and even to the business user. We believe the book will be valuable to anyone working on a Microsoft SQL Server 2005 data warehouse project.

The primary audience for this book is the new DW/BI team thats launching a project on the Microsoft SQL Server platform. We dont assume you already have experience in building a DW/BI system. We do assume you have a basic familiarity with the Microsoft world: operating systems, infrastructure components , and resources. We also assume a basic understanding of relational databases (tables, columns , simple SQL) and some familiarity with the SQL Server 2000 relational database, although thats not a requirement. Throughout the book we provide many references to other books and resources.

A second audience is the experienced Kimball Method DW/BI practitioner whos new to the Microsoft SQL Server 2005 toolset. This audience might need to do some reading to catch up on the infrastructure, especially if youve never worked on a Windows server before. Well point out which sections and chapters will be review for anyone whos read our other Toolkit books and practiced our methodology. But weve found that it doesnt hurt to read this material one more time!

Whatever your background, youll benefit most if youre just starting on a new project. While we do provide suggestions on working with existing data warehouses, in the ideal case you wont have to contend with any existing data warehouse or data martsat least none that will remain in place after the new system is deployed.



Microsoft Data Warehouse Toolkit. With SQL Server 2005 and the Microsoft Business Intelligence Toolset
The MicrosoftВ Data Warehouse Toolkit: With SQL ServerВ 2005 and the MicrosoftВ Business Intelligence Toolset
ISBN: B000YIVXC2
EAN: N/A
Year: 2006
Pages: 125

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