NEW 2-Day Instructor Led Course on Oracle Data Mining Now Available!
By Charlie Berger, Advanced Analytics-Oracle on Mar 23, 2012
UPDATED - See the updated and new Learn Predictive Analytics using Oracle Data Mining 2-day Oracle University Course.
A NEW 2-Day Instructor Led Course on Oracle Data Mining has been developed for customers and anyone wanting to learn more about data mining, predictive analytics and knowledge discovery inside the Oracle Database. To register interest in attending the class, click here and submit your preferred format.
- Explain basic data mining concepts and describe the benefits of predictive analysis
- Understand primary data mining tasks, and describe the key steps of a data mining process
- Use the Oracle Data Miner to build,evaluate, and apply multiple data mining models
- Use Oracle Data Mining's predictions and insights to address many kinds of business problems, including: Predict individual behavior, Predict values, Find co-occurring events
- Learn how to deploy data mining results for real-time access by end-users
Five reasons why you should attend this 2 day Oracle Data Mining Oracle University course. With Oracle Data Mining, a component of the Oracle Advanced Analytics Option, you will learn to gain insight and foresight to:
- Go beyond simple BI and dashboards about the past. This course will teach you about "data mining" and "predictive analytics", analytical techniques that can provide huge competitive advantage
- Take advantage of your data and investment in Oracle technology
- Leverage all the data in your data warehouse, customer data, service data, sales data, customer comments and other unstructured data, point of sale (POS) data, to build and deploy predictive models throughout the enterprise.
- Learn how to explore and understand your data and find patterns and relationships that were previously hidden
- Focus on solving strategic challenges to the business, for example, targeting "best customers" with the right offer, identifying product bundles, detecting anomalies and potential fraud, finding natural customer segments and gaining customer insight.