Predictive Analytics & Data Mining Strategic Implementation

    

Summary:
Data mining is essentially a discovery process — a process riddled with common yet elusive strategic pitfalls. Project failure is rarely due to poor model development. Rather, data mining projects often fall short of their potential due to flawed or overlooked assessment, business understanding, project definition and strategic planning specifically for information discovery.

If you are looking for an intensive vendor-neutral and non-promotional introduction to data mining best practices and an approach to predictive analytics which is critical to modeling success, then this course is designed for you. There are no prerequisites for this course. However, participants will benefit by reviewing the CRISP-DM guide ahead of the training.

“Predictive Analytics & Data Mining: Strategic Implementation” offers a concentrated presentation of capabilities, limitations, risks, rewards, use cases, best practices, strategy and lifecycle management. Those in attendance will actively step through the industry standard process for data mining and realize why an advanced degree in statistics, mathematics or computer science is no longer needed to succeed in predictive analytics. Live working sessions reveal real-world obstacles and breakthroughs from which to interpret, learn and apply.

Practitioners seeking to drill down into the tactical implementation of predictive analytics methods may also attend TMA’s Predictive Analytics & Data Mining: Model Development course. The “Model Development” course is the counterpart to this production within the series, two days immediately preceding this course at the same public venue.

Make sure to view the course series overview page to compare the two primary orientations and target the most fitting agenda for your experience, situation and objectives.

Duration:
3 Days

Audience:
IT/IS EXECUTIVES AND MANAGERS: CIOs, CKOs, CTOs, Stakeholders, Functional Officers, Technical Directors and Project Managers
LINE-OF-BUSINESS EXECUTIVES AND FUNCTIONAL MANAGERS: Risk Managers, Customer Relationship Managers, Business Forecasters, Inventory Flow Analysts, Financial Forecasters, Direct Marketing Analysts, Medical Diagnostic Analysts, eCommerce Company Executives
TECHNOLOGY PLANNERS: Who survey emerging technologies in order to prioritize corporate investment
CONSULTANTS: Whose competitive environment is intensifying and whose success requires competency with data mining and related emerging information technologies

Topics:

• Basic principles and terminology for predictive analytics
• Who is utilizing predictive analytics, and why
• What are common project pitfalls and how to avoid them
• How to define business objectives for a discovery process
• Project deployment, performance and maintenance issues
• Building confidence through hands-on participation
• How to get started

Last Update: May 18, 2013