Oracle Database 11g Data Mining Tecniques

Oracle Database 11g Data Mining Techniques Training

  • What you will learn

In Oracle Database 11g Data Mining Techniques course, students review the basic concepts of data mining and learn how leverage the predictive analytical power of the Oracle Database Data Mining option by using Oracle Data Miner 11g Release 2. The Oracle Data Miner GUI is an extension to Oracle SQL Developer 3.0 that enables data analysts to work directly with data inside the database.
The Data Miner GUI provides intuitive tools that help you to explore the data graphically, build and evaluate multiple data mining models, apply Oracle Database 11g Data Mining Techniques models to new data, and deploy Oracle Data Mining’s predictions and insights throughout the enterprise. 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 11g Data Mining Techniques, data movement is eliminated, security is maximized and information latency is minimized.

  • Objectives

  • 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
  • Audience

  •  Application Developer
  •  Database Administrators
  •  Business Analysts
  •  Data Warehouse Analyst

Key features

  • 16 hours of instructor-led training
  • 16 hours of high-quality eLearning content
  • 5 simulation exams (250 questions each)
  • 8 domain-specific test papers (10 questions each)
  • 30 CPEs offered
  • 98.6% pass rate

Oracle Database 11g Data Mining Techniques Training                    Duration :- 2 Days


  • Course Objectives
  • Suggested Course Pre-requisites
  • Suggested Course Schedule
  • Class Sample Schemas
  • Practice and Solutions Structure
  • Review location of additional resources (including ODM and SQL Developer documentation and online resources)

Overviewing Data Mining Concepts

  • 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 Oracle Data Miner 11g Release 2

Data mining with Oracle Database

  • Introducing the SQL Developer interface
  • 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
  • Creating Classification Models
  • Building the Models
  • Examining Class Build Tabs
  • Comparing the Models
  • Selecting and Examining a Model

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

Performing Market Basket Analysis

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

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 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

Deploying Data Mining Results

  • Requirements for deployment
  • Deployment Tasks
  • Examining Deployment Options
You can enroll for this classroom training online. Payments can be made using any of the following options and receipt of the same will be issued to the candidate automatically via email.

1. Online ,By deposit the mildain bank account

2. Pay by cash team training center location

Highly qualified and certified instructors with 20+ years of experience deliver more than 200+ classroom training.
Venue is finalized few weeks before the training and you will be informed via email. You can get in touch with our 24/7 support team for more details. Contact us Mob no:- 8447121833, Mail id:  [email protected] . If you are looking for an instant support, you can chat with us too.
We provide transportation or refreshments along with the training.
Contact us using the form on the right of any page on the mildain website, or select the Live Chat link. Our customer service representatives will be able to give you more details.

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good session..!!
will be useful to improve my technical Knowledge..
The concepts of the Instructor was mind-blowing…Lots of Industry examples…Very well organized…
Ajay Nunna
Nice session…!! enjoyed learning new things
Really good training. It helped me to clear a lot of doubts which were present in my mind for a long time.
“ The course content is very good and satisfactory. The trainer is also good with his teaching abilities.”
Apply the knowledge in understanding the new 11b framework setup in our system.
Apply the skill in day to day operational maintenance of our IT infrastrututre.