Predictive Analytics using Oracle Data Mining

• Explain basic data mining concepts and the benefits of predictive analysis.
• Understand primary data mining tasks and the key steps in the data mining process.
• Use Oracle Data Miner to build, evaluate, apply, and deploy multiple data mining models.
• Use Oracle Data Mining predictions and insights to address business problems.
• Deploy data mining models for batch or real-time access by end users.

1. Introduction

• Course Objectives
• Suggested Course Prerequisites
• Suggested Course Schedule
• Class Sample Schemas
• Practice and Solutions Structure
• Review location of additional resources

2. Predictive Analytics and Data Mining Concepts

• What is the Predictive Analytics?
• Introducing the Oracle Advanced Analytics (OAA) Option
• What is Data Mining?
• Why use Data Mining?
• Examples of Data Mining Applications
• Supervised Versus Unsupervised Learning
• Supported Data Mining Algorithms and Uses

3. Understanding the Data Mining Process

• Common Tasks in the Data Mining Process
• Introducing the SQL Developer interface

4. Introducing Oracle Data Miner 4.1

• Data mining with Oracle Database
• Setting up Oracle Data Miner
• Accessing the Data Miner GUI
• Identifying Data Miner interface components
• Examining Data Miner Nodes
• Previewing Data Miner Workflows

5. Using Classification Models

• Reviewing Classification Models
• Adding a Data Source to the Workflow
• Using the Data Source Wizard
• Using Explore and Graph Nodes
• Using the Column Filter Node
• Creating Classification Models
• Building the Models
• Examining Class Build Tabs

6. Using Regression Models

• Reviewing Regression Models
• Adding a Data Source to the Workflow
• Using the Data Source Wizard
• Performing Data Transformations
• Creating Regression Models
• Building the Models
• Comparing the Models
• Selecting a Model

7. Using Clustering Models

• Describing Algorithms used for Clustering Models
• Adding Data Sources to the Workflow
• Exploring Data for Patterns
• Defining and Building Clustering Models
• Comparing Model Results
• Selecting and Applying a Model
• Defining Output Format
• Examining Cluster Results

8. Performing Market Basket Analysis

• What is Market Basket Analysis?
• Reviewing Association Rules
• Creating a New Workflow
• Adding a Data Source to the Workflow
• Creating an Association Rules Model
• Defining Association Rules
• Building the Model
• Examining Test Results

9. Performing Anomaly Detection

• Reviewing the Model and Algorithm used for Anomaly Detection
• Adding Data Sources to the Workflow
• Creating the Model
• Building the Model
• Examining Test Results
• Applying the Model
• Evaluating Results

10. Mining Structured and Unstructured Data

• Dealing with Transactional Data
• Handling Aggregated (Nested) Data
• Joining and Filtering data
• Enabling mining of Text
• Examining Predictive Results

11. Using Predictive Queries

• What are Predictive Queries?
• Creating Predictive Queries
• Examining Predictive Results

12. Deploying Predictive Models

• Requirements for deployment
• Deployment Options
• Examining Deployment Options

2 Days

Course Completion Certificate by Network Binary

• Set up and access Oracle Data Miner 4.1.
• Explore the Oracle Data Miner GUI and interface components.
• Examine Data Miner nodes and workflows.
• Add data sources to workflows.
• Explore and graph data.
• Apply column filtering.
• Create and build classification models.
• Create and build regression models.
• Perform data transformations.
• Compare and select regression models.
• Create and build clustering models.
• Compare and apply clustering model results.
• Create Association Rules models for market basket analysis.
• Build and examine association-rule results.
• Create and evaluate anomaly detection models.
• Work with transactional and aggregated/nested data.
• Join and filter data.
• Enable text mining.
• Create predictive queries.
• Examine predictive results.
• Review requirements and options for deploying predictive models.

• Data Scientists
• Data Analysts
• Database Administrators

No prerequisites