How This Course Is Organised

The WebLearning Data Warehousing using Informatica 9.6.x and Oracle Data Integrator 11g Course provides hands-on step-by-step instructions on how to perform a variety of Data Warehousing and ETL Transformation tasks using Informatica and Oracle Data Integrator in an Oracle Database 11g environment for activities based on real-life work scenarios. This course combines the WebLearning Oracle Data Integrator 11g/12c: Data Warehousing and the WebLearning Informatica Data Warehousing courses.

Using the ODI graphical interfaces, you create and manage ODI repositories, which stores configuration information about the IT infrastructure, the metadata for all applications, projects, models and other ODI artifacts. You also learn how to create the ODI Topology, organize ODI models and design ODI interfaces, procedures, packages and other objects.

You will learn how to use Oracle Data Integrator Topology Manager to define context and logical schema objects according to current best practices. You will learn how to use manage projects in Oracle Data Integrator to develop interfaces and other objects. Oracle Data Integrator has an advanced metadata system which can store many types of information about your data, including constraints and Slowly-Changing Dimension information. You will also learn about the types of metadata, and how to retrieve it automatically from your database.

You will learn how to create an integration process, using Oracle Data Integrator packages. This course takes you through some of the more advanced features and uses of Oracle Data Integrator interfaces. You will also learn how to use Operator to stop, start and track the execution of Oracle Data Integrator sessions.

Using the Informatica ETL Tools, Informatica PowerCenter developers and administrators will learn about the Informatica 9.x architecture, learn how to plan, build and deploy a Data warehouse using Informatica 9.6.x as your primary ETL Tool for developing Extract, Transform and Load processes.

Using the graphical mappings, you create and manage Informatica repositories, which stores configuration information about the IT infrastructure, the metadata for all applications, projects, models and other Informatica artifacts. You also learn how to create the Informatica Topology, organize Informatica models and design Informatica mappings, procedures, workflows and other objects.

Using the PowerCenter Designer, Workflow Manager, and Workflow Monitor tools and graphical mappings, you create and manage transformations, mappings, reusable objects, sessions and workflows to extract, transform and load data. You will develop cleansing, formatting, sorting and aggregating procedures.

The WebLearning hands-on series reduces the time spent investigating what steps are required to perform a task. Because the step-by-step solutions are built for practical real world situations, not only is knowledge gained through valuable hands-on experience, but also the solutions presented may then be used as the foundation for production implementation, dramatically reducing time to deployment.

Audience

Business Intelligence Developer
Data Warehouse Administrator
Data Warehouse Analyst
Data Warehouse Developer
Technical Administrator
Systems Analysts
BI Project Leads
Data Integration Architects

Oracle Data Integrator Objectives

• Learn to Plan and Scope your ETL/ELT Projects
• Understand the ETL Development Lifecycle
• Describe the Oracle Data Integrator (ODI) system logical architecture
• Identify the system administration tools that are available for managing Oracle DI
• Overview of the architecture of the complete Oracle Data Integrator system
• Define the Oracle Data Integrator 11g (ODI) Information System architecture
• Understand Data Quality Issues in ETL Process
• Understand the architecture of the complete Oracle Data Integrator system
• Create Data Servers and Sources
• Define Physical and Logical Architecture
• Define Integration Processes
• Work with projects in Oracle Data Integrator and release your work for deployment
  Understand models, reverse-engineering model metadata from your database
• Create simple interfaces/mappings and add multiple sources to an interface/mapping
• Launch a session to run an interface/mapping
• Enforce data quality constraints in an interface/mapping
• Manage packages
• Manage and Monitor ETL processes in the ODI Console

Informatica 9.6.x Objectives

• Learn to Plan and Scope your ETL/ELT Projects
• Understand the ETL Development Lifecycle
  Understand Data Integration and ETL concepts
• Understand BI and Data warehousing Concepts 
• Understand Dimension Modelling
• Understand Data Quality Issues in ETL Process
• Understand the architecture of the Informatica system
• Design and build simple mappings and workflows
• Use PowerCenter 9.x Designer to build mappings
• Use PowerCenter 9.x Designer to extract data from a source to a target
• Use PowerCenter 9.x Designer to build transformations
• Use PowerCenter transformations to aggregate and route data to targets.
• Describe the use of Mapping Variables and Parameter Files
• Use PowerCenter 9.x Workflow Manager to build and run a workflow
• Use PowerCenter 9.x Workflow Manager to execute sessions associated with a mapping

Course Topics

Overview

Course Scenario

Introduction to Oracle Database11g

Oracle Database11g Options

Database Management Packs

Oracle Database 11g Related Products

Oracle Database11g Development Tools

Oracle SQL Developer

Navigate SQL Developer

Exploring Database Objects

SQL*Plus and SQL Workshop

Connecting to the  SQL*Plus Interface

Connecting to Databases

Configuring Database Environment

Informatica and Oracle DI Value Proposition

Informatica and Oracle DI Use-Case Scenarios

Service-Oriented Integration

Master Data Management

Introduction to Data Warehousing and Analytics Concepts

Understanding ETL and Data Warehousing

Understanding Business Intelligence

Understanding OLAP and Data Mining

Data Integration Concepts

Consolidation, Normalisation, and Standardisation

Data Integration Paradigms (ETL and ELT)

ETL Processing Categories

Incremental Loads

Detecting Net Changes

Data Integration Management Concepts

Batch Processing and the Enterprise ETL Schedule

ETL Patterns

Data Quality

Introduction to Information and Data Quality

Total Information Quality Management

Establishing the Information Quality Environment

Assessing Data Definition and Information Architecture Quality

Introduction to Enterprise Data Quality Integration Platforms

Oracle Data Warehouse Components

Data Warehouses, Business Intelligence, Data Marts, and OLTP

Typical Data Warehouse Components

Warehouse Development Approaches

Extraction, Transformation, and Loading (ETL)

The Dimensional Model and Oracle OLAP

Informatica PowerCenter and Architecture

Oracle Warehouse Builder

Oracle Data Integrator

Oracle Database OLAP Option

Oracle Data Mining

Oracle BIEE

Oracle BI Publisher

Data Warehouse Concepts and Terminology

Data Warehouse Definition and Properties

Data Warehouse Versus OLTP

Data Warehouses Versus Data Marts

Typical Data Warehouse Components

Data Warehousing Process Components

Data Warehouse Modelling Concepts

Modelling for Analytics and Data Warehouses

Normalisation

3rd normal Form

Dimensional Modelling

Fact tables

Types of Fact Tables

Dimension Tables

Star Schema

Snowflake Models

Constellation Models

Conformed Dimensions

Alternate Dimensions

Degenerate Dimensions

Junk Dimensions

Slowly Changing Dimensions

Surrogate keys

Data Warehousing Deployment Approaches

Warehouse Bus Architecture

Centralised Data Warehouse Approach

Hub and Spoke Approach

Approach to Informatica and Oracle DI Warehouse Development

Strategy and Planning Phase

Discover Phase

Analyse Phase

Define Phase

Develop Phase

Deploy Phase

Modelling the Data Warehouse:Logical Model

Business, Logical, Dimensional, and Physical Modeling

Data Warehouse Modeling Issues

Defining the Business Model

Defining the Logical Model

Defining the Dimensional Model

Modelling the Data Warehouse:Physical Model

Defining the Physical Model

Star, Snowflake, and Third Normal Form

Fact and Dimension Tables Characteristics

Translating Business Dimensions into Dimension Tables

Translating Dimensional Model to Physical Model

Database Sizing, Storage, Performance, and Security Considerations

Database Sizing and Estimating and Validating the Database Size

Oracle Database Architectural Advantages

Data Partitioning

Indexing

Optimizing Star Queries

Tuning Star Queries

Parallelism

Security in Data Warehouses

Oracle  Data Warehouse Security

The ETL Process: Extracting Data

Extraction, Transformation, and Loading (ETL) Process

ETL: Tasks, Importance, and Cost

Extracting Data and Examining Data Sources

Mapping Data

Logical and Physical Extraction Methods

Extraction Techniques and Maintaining Extraction Metadata

Possible ETL Failures and Maintaining ETL Quality

ETL Tools

Oracle Data Integrator

Informatica PowerCenter

Data Oracle Warehouse Builder

SQL*Loader

Data Pump

The ETL Process: Transforming Data

Transformation

Remote and Onsite Staging Models

Data Anomalies

Transformation Routines

Transforming Data: Problems and Solutions

Quality Data: Importance and Benefits

Transformation Techniques and Tools

Maintaining Transformation Metadata

The ETL Process: Loading Data

Loading Data into the Warehouse

Transportation Using Flat Files, Distributed Systems, and Transportable Tablespaces

Data Refresh Models: Extract Processing Environment

Building the Loading Process

Data Granularity

Loading Techniques Provided by Oracle and Informatica

Loading Techniques in Oracle Data Integrator 11g

Loading Techniques in Informatica PowerCenter 9.6.x

Postprocessing of Loaded Data

Indexing and Sorting Data and Verifying Data Integrity

Refreshing the Warehouse Data

Developing a Refresh Strategy for Capturing Changed Data

User Requirements and Assistance

Load Window Requirements

Planning and Scheduling the Load Window

Capturing Changed Data for Refresh

Time- and Date-Stamping, Database triggers, and Database Logs

Applying the Changes to Data

Materialized Views

Using Summaries to Improve Performance

Using Materialized Views for Summary Management

Types of Materialized Views

Build Modes and Refresh Modes

Query Rewrite: Overview

Cost-Based Query Rewrite Process

Working With Dimensions and Hierarchies

Metadata  Management

Defining Warehouse Metadata

Metadata Users and Types

Examining Metadata: ETL Metadata

Extraction, Transformation, and Loading Metadata

Defining Metadata Goals and Intended Usage

Identifying Target Metadata Users 

Choosing Metadata Tools and Techniques

Integrating Multiple Sets of Metadata

Managing Changes to Metadata

NOTE: THIS COURSE IS ALSO AVAILABLE IN SELF-STUDY E-LEARNING, CBT OR DISTANCE LEARNING FORMATS. FEEL FREE TO ASK IF YOU PREFER DISTANCE, E-LEARNING OR CBT LEARNING  FORMATS. PRICES DIFFER

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