The Importance of Data Warehousing
Today, data warehousing in some form has become a given, a must, for running an enterprise of any significant size. At its best, it enables actual competitive advantage, but even when focused more tactically or departmentally, it is now considered essential to being competitive—as basic and essential as the general ledger or payroll system. While it is often difficult to quantify the benefits of data warehousing in terms of return on investment (ROI), no one these days seriously questions its value and necessity. As a database developer, you are likely to be involved with data warehousing in one way or another—if not directly, at least in interfacing to a data warehouse. So it’s important for you to understand what data warehousing is all about.
Developing a data warehouse is in some ways a very different undertaking from traditional online transactional processing (OLTP) database development, with which you are probably more familiar. Two of the most notable differences are that data warehousing essentially emphasizes data and its relationships—as opposed to the emphasis on process found in the typical OLTP application—and that hard experience by practitioners has evolved specialized ways of modeling data that are particularly useful in achieving the goals of data warehousing.
Even if your role is primarily technical, you will be able to do a much better job of building or interfacing to a data warehouse if you know something about these differences from OLTP and the reasons for them. This will also help you appreciate the perspective of decision makers who rely on accurate data storage and analysis (see the next chapter), which will be very likely different from that of typical OLTP application stakeholders.
Data warehousing is an essential foundation for what has come to be known as business intelligence (BI). We’ll learn more about the close relationship between data warehousing and BI later in this chapter, but for now, appreciate that they are not synonymous. At the same time, in keeping with our earlier observation, mentally substitute enterprise when you hear business.
The remainder of this chapter consists of five sections that build upon one another as we progress through our treatment of data warehousing. Instead of immediately focusing on technical details and step-by-step procedures in SQL Server 2008, we review the history leading up to why data warehousing is today a distinct practice and how SQL Server 2008 represents an excellent data warehousing platform.
The first section, “What Preceded Data Warehousing,” focuses on the origins of data warehousing to help you appreciate why data warehousing emerged as a distinct practice responding to industry issues. The second section, “Data Warehouse Design,” describes the two principal approaches to data warehouse design. The third section, “What Data Warehousing Is Not,” considers various terms often confused with data warehousing and gives them distinct definitions. The fourth section, “Practical Advice About Data Warehousing,” alerts you to various common but nonobvious issues that you might encounter when building a data warehouse. Last, the fifth section, “SQL Server 2008 and Data Warehousing,” discusses SQL Server 2008–specific details as they relate to data warehousing.
With this ambitious agenda to cover in just a single chapter, we will not actually tell you much about “how” to build the perfect data warehouse—dozens of entire books are available for that. Rather, what we aim to provide is a unique combination of background, clarification of terms, identification of tricky spots, and finally some technical details about the specific data warehousing platform offered by SQL Server 2008.