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Course Descriptions

Currently accepting applications Apply now >> Next program starts: Autumn 2008 Program location: Bellevue Sign up to receive e-mail updates >> Contact a program representative >>   Program at a glance >>

Prerequisites

Students wishing to take this certificate program are required to have a minimum of two years of business experience working in a mid-to-large organization, or for the public sector. You must also first complete the SQL Self-Test before enrolling in any of the courses below. Enrollment in each course requires completion of the previous course in this series.

Interested in taking a single class? Some courses (designated by a below) may be open on a space-available basis to professionals who are not seeking the certificate. See Single-Course Enrollment for details.

Autumn Course

Business Intelligence: Concepts and Principles

Schedule: Thursdays, 6:00-9:00 p.m., Oct. 2-Dec. 11, 2008 (no class on Nov. 27); Orientation, Thursday, 5:30-6:00 p.m., Oct. 2, 2008; 3.0 CEUs.
Instructor: Nichols.

This course introduces BI topics and discusses similarities and differences to competitive intelligence, knowledge management, and computational linguistics. The course also discusses the states of a BI project, introduces the technologies, and provides an overview of topics that will then serve as the foundation for the in-depth project planning and implementation concepts applied in courses two and three.

This course will discuss the various stages of a BI project: justification, planning, business analysis, design, construction, and deployment. It will also explore important BI questions, such as, 'Who are the vendors?', 'What is on the horizon for BI?', and 'How can this information be strategically used to assist in sound business planning and forecasting?'.

Other topics include:

• Knowledge management
• Content management
• Competitive intelligence
• An overview of computational linguistics & handling unstructured data
• Business modeling; what-if analysis
• Project management
• Data management and relational databases
• Analysis vs. reporting
• Spatial analysis
• High dimensional visualization
• Data mining and types of data mining models
• Information and retrieval
• Metadata and master data management (MDM)
• OLAP and multi-dimensional modeling
• Data warehouses
• ETL and data preparation
• Customer relationship management and an overview of CRM Systems
• Planning and forecasting methods

How to sign up for individual enrollment in this course

Winter Course

Data Warehouse: Project Planning, Analysis and Design

Schedule: Saturdays, 9:00 a.m.-4:00 p.m., Jan. 10 and 24, Feb. 7 and 21, and Mar. 7, 2009; 3.0 CEUs.
Instructor: Vitt.

This course focuses on how to design and build a Business Intelligence solution.

We will introduce and compare various BI technologies across key BI Platform, BI Pure Play, and ERP vendors such as Microsoft, Oracle, Teradata, and Cognos.

You will also learn how to design and build a data warehouse within the context of student BI projects. Students can develop their own projects within collaborative teams or be assigned an existing data source to develop a project. To ensure success during the implementation phase in course three, students will plan for and gather business requirements, as well as design the data warehouse in order to develop an effective BI plan.

Other topics include:

• Defining the BI project
• Scoping the project down
• Asking the right questions
• Data modeling
• Analysis of reports & metrics
• Gathering business requirements
• Project analysis
• Defining needed dimensional measures
• Warehouse design
• Sourcing the data and source mapping to the target location

How to sign up for individual enrollment in this course

Spring Course

Data Warehouse: Project Implementation

Schedule: Wednesdays, 6:00-9:00 p.m., Apr. 8-June 10, 2009; 3.0 CEUs.
Instructor: Root.

This course takes the planning strategies that students developed in the previous course and uses those to develop and implement a successful BI project. They will build the data warehouse, prepare the data and load it into the warehouse followed by modeling strategies, analysis, and testing. Student will work on teams to simulate real-world scenarios to implement the project.

Other topics include:

• Developing a schema
• Building & tuning the data warehouse
• Data preparation & ETL
• OLAP & multidimensional modeling
• Analysis & reporting
• Testing strategies & developing an effective testing plan
• Student project demonstrations