Prerequisite:   Predictive Analytics (recommended)

 

Two-Day Course

Course Outline

You Will Learn

• The data mining process and general implementation
• How to prepare raw data and benefit from visualization
• Various data mining methods and how they compare
• Advanced model building techniques
• Results analysis and validation
• Technology and product selection
• Solution integration, ongoing performance and maintenance
• Where to begin and how to obtain resources and support

Geared To

• IT PROFESSIONALS who wish to expand their skills in this increasingly visible area within the corporate IT agenda
• PROJECT LEADERS who must report on developmental progress, resource requirements and system performance
• DECISION SUPPORT SYSTEM ARCHITECTS who require a solid understanding of the infrastructures required for supporting a data mining solution
• BUSINESS ANALYSTS who must develop and interpret the models, communicate the results and make actionable recommendations
• FUNCTIONAL ANALYSTS: Customer Relationship Managers, Risk Analysts, Business Forecasters, Statistical Analysts, Inventory Flow Analysts, Direct Marketing Analysts, Medical Diagnostic Analysts, Market Timers, e-commerce System Architects and Web Data Analysts

This two-day course presents an in-depth examination of the data mining process at a functional level. Attendees will observe and participate in demonstrations of computer-guided analytical techniques for extracting and interpreting complex business rules from data. If you desire a rapid and substantial boost in your understanding of data mining concepts, tools, techniques and supporting methods, then this course is designed for you.

The rapid emergence of electronic data processing and collection methods has lead some to call recent times as the "Information Age." However, it may be more accurately termed as "The Age of the Data Glut." Most businesses either posses a large database or have access to one. These databases contain so much data that it becomes very difficult to understand what that data is telling us.

There is hardly a transaction that does not generate a computer record somewhere. All this data has meaning with respect to making better business decisions or understanding customer needs and preferences. But how do you discover those needs and preferences in a database that contains gigabits of seemingly incomprehensible numbers and facts? Data mining does just that.

The intent of this course is to offer attendees a stronger grasp of data mining techniques, and a solid understanding of how various methods and tools apply to different kinds of data intensive problems. Among the benefits of attending this course, you will:

• Experience vendor-neutral exposure to tools and techniques that will place you months ahead in method planning and product surveying
• Examine which methods and tools are most effective for your needs
• Avoid pitfalls in data preparation, modeling, and results interpretation
• Leave with resources, contacts and actionable plans to substantially increase your analysis capabilities while minimizing dead ends

This course does not restrict or skew the presentation of data mining methods through a single product. Rather, the course gives consideration to all resources from a vendor-neutral position. The instructor has over ten years of experience in applying data mining technology to real-world applications.

In addition, live modeling demonstrations will support the instructional sessions. The demonstrations will highlight superior performance as well as pitfalls. The instructor will show how to evaluate various packages based on strengths, limitations, value and general performance

Those who have not recently been exposed to analytical software, statistical methods or modeling terminology may benefit by obtaining a solid platform through the Predictive Analytics: A Strategic Overview course. Likewise, participants who wish to apply the techniques and methods presented in this course in a hands-on workshop environment through team-oriented exercises should consider the Hands-On Data Mining Application Workshop following this course.