Chapter 12: Data Warehouse Concepts

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Overview

After completing this chapter, you will be able to:

• Learn the objectives and characteristics of a functional data warehouse.

• Learn the goals of a business intelligence solution.

• Distinguish the differences between operational and decision support systems.

• Understand the role of data granularity in data warehouse design.

• Define facts, aggregations, and dimensions.

• Discuss proper assessment of data quality, update frequency, and persistence.

• Review ETL architecture options.

Microsoft SQL Server Integration Services (SSIS) will support many different types of database solutions. You might find SSIS useful to import spreadsheet data into your customer management system or to combine invoice records into a central billing system. However, the most common, complete business solution involving significant data transformation is a decision-support data warehouse for reporting and data analysis. As businesses grow and need to analyze and report on more data, a data warehouse becomes necessary to house the increasing volume of data derived from different operational sources. Unlike the occasional need to import and combine data from spreadsheets and other source files, extracting, transforming, and loading data from operational databases into a central data warehouse is a routine business process that must be optimized and performed on a regular schedule.