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Informatica 9.6.x and Oracle Data Integrator 11g: Data Warehousing


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Available On Demand
N/A
240 Hours over 6 Months
Bespoke Course (Online)
-
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£449.00
ETL Developers, Data Scientists, Data Warehouse Administrator, Data Warehouse Analyst, Data Warehouse Developer, BI Developer, Functional Implementer, Project Manager, Support Engineer
Online / Distance Learning Course

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


Course Objectives for ODI 11g/12c:

Learn to Plan your ETL/ELT Projects
Understand the ETL Development Lifecycle
Understand basic Data warehousing Concepts
Understand basic Dimension Modelling
Understand Data Quality Issues in ETL Process
Understand the architecture of the complete Oracle Data Integrator system
Define Data Sources
Define Physical and Logical Architecture
Create and reverse-engineer models
Understand models, reverse-engineering model metadata from your database
Manage metadata in Oracle Data Integrator: models and data quality
Create simple interfaces and add multiple sources to an interface
Launch a session to run an interface
Enforce data quality constraints in an interface
Manage packages


Course Objectives for Informatica 9.6.x/Cloud

Understand the Informatica Data Warehouse and ETL Development Lifecycle
Understand the BI and Warehouse Development Process
Learn to Manage Informatica Warehouse Projects
Understand Data warehousing Concepts
Understand Dimension Modelling
Understand Data Quality Issues in ETL Process
Understand the architecture of the Informatica system
Manage your Informatica environment using the Informatica Console
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 cleanse, format and join data
Use PowerCenter transformations to aggregate and route data to targets.
Perform error handling/trapping using PowerCenter mappings
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

 

This is a 6 Months course and Includes a Free eBook and six months access to a personal Tutor for support on-line.


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