Oracle Database 19c: Data Mining Techniques Course Overview

Oracle Database 19c: Data Mining Techniques Course Overview

The Oracle Database 19c: Data Mining Techniques course is designed to educate learners on the comprehensive features of data mining within the Oracle Database environment. It begins with an Introduction to the fundamental concepts, providing a solid foundation for understanding data mining. The course progresses to Data Mining Concepts and Terminology, clarifying the key terms and principles used in the field.

In The Data Mining Process module, learners are guided through the steps involved in mining data effectively. Oracle Data Miner is introduced, demonstrating how to leverage this tool for mining tasks. The course then delves into practical applications, teaching students about Classification Models, Regression Models, and Clustering Models. Each model is essential for predicting outcomes, trends, and segmenting data.

Advanced techniques like Market Basket Analysis and Anomaly Detection are covered, equipping learners with skills to uncover patterns and outliers. Finally, the course emphasizes the importance of Deploying Data Mining Results, ensuring that the insights gained are effectively integrated into business processes. By completing this course, learners will be able to apply robust data mining techniques using Oracle Database 19c, turning data into actionable intelligence.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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Course Prerequisites

Certainly! The Oracle Database 19c: Data Mining Techniques course is designed to provide in-depth knowledge and practical skills on how to use data mining to discover insights, make predictions, and leverage Oracle Database for analytics. To ensure that participants can successfully undertake and benefit from this training, the following prerequisites are recommended:

  • Basic understanding of database concepts: Familiarity with relational database management systems (RDBMS) and the fundamentals of how databases store and manage data is essential for grasping the concepts taught in the course.

  • Knowledge of SQL: Participants should have a working knowledge of SQL (Structured Query Language), as it is commonly used for data manipulation and analysis within Oracle Database.

  • Familiarity with Oracle Database: Having some prior experience with Oracle Database, even at an introductory level, will help participants understand the context and application of data mining techniques within the Oracle environment.

  • Understanding of basic statistical concepts: A grasp of fundamental statistics, including measures of central tendency, dispersion, and the concept of distributions, will assist in understanding data mining algorithms and interpreting results.

  • Analytical mindset: An interest in problem-solving and analytical thinking will enable participants to engage with the course material and apply data mining techniques effectively.

These prerequisites are intended to provide a foundation for the course material and help ensure that participants can keep pace with the instruction and fully comprehend the data mining techniques being taught.

Target Audience for Oracle Database 19c: Data Mining Techniques

  1. The Oracle Database 19c: Data Mining Techniques course equips learners with advanced data analysis skills using Oracle's tools.

  2. Target Audience and Job Roles:

  • Data Scientists
  • Database Administrators (DBAs) with a focus on analytics
  • Data Analysts
  • Business Intelligence (BI) Professionals
  • IT Professionals interested in data mining
  • Data Engineers
  • Database Developers
  • Analytics Consultants
  • Machine Learning Engineers
  • Research Scientists (in the field of data)
  • Data Warehousing Specialists
  • Students studying computer science or data-related courses

Learning Objectives - What you will Learn in this Oracle Database 19c: Data Mining Techniques?

Brief Introduction to the Course's Learning Outcomes and Concepts Covered:

Gain in-depth knowledge of Oracle Database 19c Data Mining techniques, including the process, tools, and models essential for extracting insights from complex data sets.

Learning Objectives and Outcomes:

  • Understand the fundamental concepts and terminology of data mining.
  • Learn the steps involved in the data mining process from pre-processing to model evaluation.
  • Gain proficiency in using Oracle Data Miner to create, evaluate, and deploy data mining projects.
  • Develop skills to apply classification models for predicting categorical outcomes and understand their evaluation metrics.
  • Acquire knowledge on regression models to predict continuous outcomes and assess model performance.
  • Understand clustering techniques to discover natural groupings in data and interpret the results.
  • Learn to perform Market Basket Analysis to uncover associations between items in transactional data.
  • Gain the ability to detect anomalies in data using appropriate data mining models.
  • Master the deployment of data mining results into real-world applications for decision-making.
  • Acquire practical experience through hands-on exercises in each module to reinforce learning and competency in Oracle Data Mining.