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Get Started
The Autumn 2009 program is no longer accepting applications
Next program starts: Autumn 2010
Details will be posted in Spring
Single courses may be available
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Courses represent a mix of lecture, demonstration, group work, case studies, and project-based learning, The program consists of one course per quarter where a class meets one evening per week in downtown Seattle.
Prerequisites
Students wishing to take this certificate program are required to meet the following prerequisites:
- Proficiency with using pivot tables in Microsoft Excel (or another spreadsheet package)
- Ability to use or produce reports, graphs, and charts from spreadsheets or other analytical tools
- Basic SQL - completion of SQL Self-Test required
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
Data Visualization
Schedule: Mondays, 6:00-9:00 p.m., Oct. 12-Dec. 14, 2009;
$679; 3.0 CEUs.
Instructor: Michael Luckevich.
We all intuitively believe that fact-based decision making is good, but we often lack the right skills required to present quantitative information in a meaningful way. Although tables and graphs are widely used, the presentation is often poorly designed-misrepresenting or obfuscating the truth. Why? Because almost no one, including financial analysts or business intelligence professionals, have been trained in information design and leveraging visualization techniques to help support better decision making.
This course teaches information design fundamentals and introduces a variety of visualization tools and techniques. At the end of the course, the student will be able to identify which visualization technique will drive the most impact under a variety of scenarios. The student will also learn how to present meaningful information in the most compelling and consumable fashion.
Course Topics:
- Fact Based Decision Making - Why Bother?
- Discuss benefits
- Discuss importance of linkages to strategy
- Define key terms - like Key Performance Indicators, etc.
- Fundamentals of Information Design
- BI vs. Search
- Data Visualization/Presentation/Exploration Techniques and Tools - possibly include demonstrations of each - likely broken into several classes -maybe one to cover design techniques for each topic
- Overview of all visualization techniques and tools which can be used to support each style
- Deep dive into Charts, Graphs, and Tables
- Dashboards
- Scorecards
- Data Mining
- Ad-Hoc Exploration
- Driving Information Impact by Using Appropriate Visualization Technique
- Dealing with Data Quality Issues
- Visualization Case Studies
How to sign up for individual enrollment in this course
Winter Course
Data Analysis
Schedule: Mondays, 6:00 p.m.-9:20 p.m., Jan. 4- Mar. 15, 2010 (no class Jan. 18 and Feb. 15); $679; 3.0 CEUs.
Instructor: Brian Miller.
Deriving value from data is a core challenge facing many organizations. Successfully organizing large data volumes into meaningful and intuitive business models require the skills of both business and technical resources. While business analysts well understand the organizational value of data and how it can be used to solve key business issues, technical resources provide the scalable data infrastructure that integrates and cleanses data to support the business in a timely and predictable manner.
While each group brings strong skills to the table, business intelligence projects can quickly break down when these groups do not share a common data vision. To solve this problem, this course focuses on how you can use Online Analytical Processing (OLAP) technologies to bridge the data gap between business and technical data experts. For business analysts, this course enables you to understand the data challenges as well as the technologies that are available to handle data obstacles. For technical professionals, this course provides you with better insight into how you can explain the benefits and challenges of BI technologies to a non technical audience.
To provide the framework for the course, concepts will be explained and demonstrated in real world business scenarios such as sales, marketing, operations, finance, supply chain, and other functional areas across a variety of industries.
Course Topics:
- Bridging the Data Gap with OLAP Technologies - Fast Query Performance (Aggregation Management, Caching, Multi-Dimensional Analysis, Advanced Analytics (Planning / Forecasting)
- Multidimensional Design Principles (Dimensions, Hierarchies, Attributes)
- Measure / Calculations Design
- General Types of OLAP Analyses / Features (Variance Analysis, What If Analysis, Time Series, Statistical, Allocations, Currency Conversions, Exception Highlighting)
- Storing Textual Data (Commentary on performance)
- BI Vendor Comparison of OLAP Definitions and Implementations
- Application Specific OLAP (Sales/Marketing, CRM, Planning and Forecasting, Financial Reporting)
- Hardware Architecture
- Correlated Topics - Reporting and Analysis Tools, Data Visualization, OLAP vs. Data Mining, Master Data Management (MDM)
- Deployment Challenges (OLAP Technical Architectures, Data Volumes,Real Time Data, Data Cleanliness, Data Profiling, History, Data explosion, Scalability and Performance, Security
How to sign up for individual enrollment in this course
Spring Course
Data Mining
Schedule: Mondays, 6:00-9:00 p.m., March 29-June 7, 2010; $679; 3.0 CEUs.
Instructor: Darwin Schweitzer.
This course teaches the fundamental principles of data mining and introduces a range of tools and techniques - from spreadsheets to specialized applications. This course will introduce the student to Microsoft’s SQL Server 2008 Analysis Services Data Mining capabilities and the Data Mining Add-in for Microsoft Excel 2007.
Course topics included are:
- An introduction and overview of Data Mining
- Data Mining Concepts
- Data Mining using the Data Mining Add-in for Microsoft Excel 2007
- Using SQL Server Data Mining
- Data Mining Algorithms
- Business Problems for Data Mining
- Data Mining Tasks
- Data Mining with SQL Server Integration Services
- Vendor Analysis of Data Mining Tools
How to sign up for individual enrollment in this course
