Data Mining: A Practical look at Data Preparation
Data Mining is a process that can allow companies to turn their data into meaningful information about customers facilitating CRM and other business activities. Data Mining is a cyclical process that starts with identifying the business problem, transforming data into information, acting on the information, and measuring the results. Arguably, one of the most challenging aspects of Data Mining is that of data preparation. Data must be sourced, integrated, cleansed and prepared for Data Mining activities. This presentation, after giving a brief overview of what Data Mining is and how it is applied, will look in detail at data preparation for Data Mining. It will walk through a real world case in order to illustrate the various options and present the solution that was utilized and discuss the lessons learned.
- A Crash Course in Data Mining
- a. What is Data Mining
- b. Applications of Data Mining
- c. Getting the Data for Data Mining
- Data Preparation for Data Mining: A Case Study
- a. The Environment: The Data Environment & The Organizational Environment
- b. The Requirements
- c. The Assessment: Sourcing the Data & Prioritizing the Requirements
- d. The Design: Options & End Result: An inverse Star Schema?
- Lessons Learned
- Wrap Up
Jason Brown is a consultant with the Data Warehousing and Business Intelligence practice of Cognicase (www.cognicase.com), an IT solutions provider specializing in the development and integration of transactional solutions. Jason has an MBA specializing in Information Systems Management and nearly 5 years of IT consulting experience, mostly in the Telecommunications sector. Jason has been involved in Data Warehousing for the past 2 years on several initiatives. On one recent project Jason led the assessment and design for a Data Mining project at a mobile phone company.
Jason Brown, Data Mining: A Practical look at Data Preparation
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