oracle 200x118 wht
8420  Reviews star_rate star_rate star_rate star_rate star_half

Predictive Analytics using Oracle Data Mining Ed 1

This Predictive Analytics using Oracle Data Mining Ed 1 training will review the basic concepts of data mining. Expert Oracle University instructors will teach you how to leverage the predictive...

Read More
By Request
$2,700 USD
Duration 2 days
Course Code D91318GC10
Available Formats Classroom

Overview

This Predictive Analytics using Oracle Data Mining Ed 1 training will review the basic concepts of data mining. Expert Oracle University instructors will teach you how to leverage the predictive analytical power of Oracle Data Mining, a component of the Oracle Advanced Analytics option.

Learn To:

  • 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, apply, and deploy multiple data mining models.
  • Use Oracle Data Mining's predictions and insights to address many kinds of business problems.
  • Deploy data mining models for end-user access, in batch or real-time, and within applications.

Benefits to You

When you've completed this course, you'll be able to use the Oracle Data Miner 4.1, the Oracle Data Mining "workflow" GUI, which enables data analysts to work directly with data inside the database. The Data Miner GUI provides intuitive tools that help you explore the data graphically, build and evaluate multiple data mining models, apply Oracle Data Mining models to new data, and deploy Oracle Data Mining's predictions and insights throughout the enterprise.

Oracle Data Miner's SQL APIs - Get Results in Real-Time

Oracle Data Miner's SQL APIs automatically mine Oracle data and deploy results in real-time. Because the data, models, and results remain in the Oracle Database, data movement is eliminated, security is maximized and information latency is minimized.

Skills Gained

  • 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, apply, and deploy multiple data mining models
  • Use Oracle Data Mining's predictions and insights to address many kinds of business problems
  • Deploy data mining models for batch or real-time access by end-users

Who Can Benefit

  • Analyst
  • Data Scientist
  • Database Administrator

Course Details

Topics

  • Introduction
    • Course Objectives
    • Suggested Course Prerequisites
    • Suggested Course Schedule
    • Class Sample Schemas
    • Practice and Solutions Structure
    • Review location of additional resources
  • Predictive Analytics and Data Mining Concepts
    • What is the Predictive Analytics?
    • Introducting 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
  • Understanding the Data Mining Process
    • Common Tasks in the Data Mining Process
    • Introducing the SQL Developer interface
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Mining Structured and Unstructured Data
    • Dealing with Transactional Data
    • Handling Aggregated (Nested) Data
    • Joining and Filtering data
    • Enabling mining of Text
    • Examining Predictive Results
  • Using Predictive Queries
    • What are Predictive Queries?
    • Creating Predictive Queries
    • Examining Predictive Results
  • Deploying Predictive models
    • Requirements for deployment
    • Deployment Options
    • Examining Deployment Options
  • Course Objectives
  • Suggested Course Prerequisites
  • Suggested Course Schedule
  • Class Sample Schemas
  • Practice and Solutions Structure
  • Review location of additional resources

Predictive Analytics and Data Mining Concepts

  • What is the Predictive Analytics?
  • Introducting 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

Understanding the Data Mining Process

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

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

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

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

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

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

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

Mining Structured and Unstructured Data

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

Using Predictive Queries

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

Deploying Predictive models

  • Requirements for deployment
  • Deployment Options
  • Examining Deployment Options
Read Less

Schedule

Upcoming Course Dates

There are currently no scheduled dates for this course. If you are interested in this course, contact us with the form below.

Contact Information
Ascendient Learning would like to occasionally share news about our services and career opportunities via e-mail when we believe it would be relevant to you. Would you like to opt-in to these communications? You may withdraw your consent at any time using the opt-out/preferences link in the emails sent.

FAQ

Does the course schedule include a Lunchbreak?

Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does Ascendient Learning deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

What does vendor-authorized training mean?

As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.

Is the training too basic, or will you go deep into technology?

It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.

How up-to-date are your courses and support materials?

We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.

Are your instructors seasoned trainers who have deep knowledge of the training topic?

Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.

Do you provide hands-on training and exercises in an actual lab environment?

Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.

Will you customize the training for our company’s specific needs and goals?

We will work with you to identify training needs and areas of growth.  We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.

How do I get started with certification?

Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.

Will I get access to content after I complete a course?

You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.

How do I request a W9 for Ascendient Learning?

View our filing status and how to request a W9.

Reviews

vary good online learning. instructor is vary good the way he explained every thing.

very good and spcecific course and above all a very good instructor. In few days I have learned a lot.

Some Labs are very good but some steps it ask to update but its already updated, but overall its very good training.

this class was informative, made me think about certifying for the suse manager cert.

Exit certified was great as it is very in depth and hands on learning which made it very easy to learn this type of work.