Business Intelligence & Data Warehousing

Learn how to make better business decisions, use fewer resources, and improve your company's bottom line by developing and using a data warehouse. This course provides an overview of business intelligence and data warehousing and gives you a look at all the major facets of developing and using a data warehouse to make effective business decisions. You'll work on a single project that allows you to develop a project plan and business case for a data warehouse, develop a dimensional model, develop a data staging process, and develop a data access process. You'll also learn about careers working with business intelligence and data warehousing as well as the educational requirements for this field.

Learn how to build a high performance dimensional data model. A good dimensional model and its physical database form the hub of a business intelligence data warehouse, serving as the target of the data integration and as the source of business intelligence data. This course provides both introductory and advanced concepts and techniques for developing effective dimensional models. Learn how to design dimensional models for extensibility, employ a proven dimensional design process, apply the process to several representative situations, and understand a variety of advanced dimensional modeling techniques.

The Extract, Transform, and Load (ETL) process is typically the most time-consuming, misunderstood, and underestimated task in building a data warehouse and other data integration applications. The ETL process addresses and resolves the challenges of extracting data from disparate operational source systems, storing it in the data staging area, profiling data for errors, cleaning and transforming the data, and mass loading it into the target enterprise data warehouse, data marts, or operational systems. Source systems may include mainframe, relational, ERP/CRM, real-time, web, and desktop systems. Microsoft SQL Server Data Transformation Services (DTS) will be used as the ETL tool for workshops and homework assignments. Prior knowledge of DTS is helpful but not required.