Informatica Training

Informatica Class Chennai provides real-time and placement focused Informatica training in chennai with real-time project scenarios. We can guarantee classes that makes you as a Informatica Expert. The Best Informatica Training course that is exclusively designed with Basics through Advanced Data warehousing Concepts. Informatica Certification and Interview Guidance are provided during the course. All our training sessions are Completely Practical and Real Time.

Special Offer for this month :: Analytic SQL + Informatica + UNIX with a discount price of Rs. 12,000/-

Learn how to use Informatica from beginner level to advanced techniques which is taught by experienced working professionals. With our Informatica Training in Chennai you will learn concepts in expert level with practical scenarios.

Informatica Training in Chennai

Best Institute for Informatica Training in Chennai provided by Real time working Experts. Informatica Training, ETL Tool Training, Data Modeling Training, Informatica Training with real-world ETL process implementations organized in Informatica training classes.
Greens Technology in Adyar is the Best Informatica training institute in Chennai offers Hands-On Informatica courses in Chennai with Job Placement by ETL professionals having Informatica projects experience using ETL and Business Intelligence for more than 10 years. All our sessions are completely practical and interactive paired with Realtime Methodologies, Project Scenarios and Case studies exclusively on Informatica.

Informatica Training Course Content

Analytic SQL for Data Warehousing

  • Course Objectives, Course Agenda and Class Account Information
  • Describe the Schemas and Appendices used in the Lesson
  • Overview of SQL*Plus Environment
  • Overview of SQL Developer
  • Overview of Analytic SQL
  • Oracle Database SQL and Data Warehousing Documentation

Grouping and Aggregating Data Using SQL

  • Generating Reports by Grouping Related Data
  • Review of Group Functions
  • Reviewing GROUP BY and HAVING Clause
  • Using the ROLLUP and CUBE Operators
  • Using the GROUPING Function
  • Working with GROUPING SET Operators and Composite Columns
  • Using Concatenated Groupings with Example

Hierarchical Retrieval

  • Using Hierarchical Queries
  • Sample Data from the EMPLOYEES Table
  • Natural Tree Structure
  • Hierarchical Queries: Syntax
  • Walking the Tree: Specifying the Starting Point
  • Walking the Tree: Specifying the Direction of the Query
  • Using the WITH Clause
  • Hierarchical Query Example: Using the CONNECT BY Clause

Working with Regular Expressions

  • Introducing Regular Expressions
  • Using the Regular Expressions Functions and Conditions in SQL and PL/SQL
  • Introducing Metacharacters
  • Using Metacharacters with Regular Expressions
  • Regular Expressions Functions and Conditions: Syntax
  • Performing a Basic Search Using the REGEXP_LIKE Condition
  • Finding Patterns Using the REGEXP_INSTR Function
  • Extracting Substrings Using the REGEXP_SUBSTR Function

Analyzing and Reporting Data Using SQL

  • Overview of SQL for Analysis and Reporting Functions
  • Using Analytic Functions
  • Using the Ranking Functions
  • Using Reporting Functions

Performing Pivoting and Unpivoting Operations

  • Performing Pivoting Operations
  • Using the PIVOT and UNPIVOT Clauses
  • Pivoting on the QUARTER Column: Conceptual Example
  • Performing Unpivoting Operations
  • Using the UNPIVOT Clause Columns in an UNPIVOT Operation
  • Creating a New Pivot Table: Example

Pattern Matching using SQL

  • Row Pattern Navigation Operations
  • Handling Empty Matches or Unmatched Rows
  • Excluding Portions of the Pattern from the Output
  • Expressing All Permutations
  • Rules and Restrictions in Pattern Matching
  • Examples of Pattern Matching

Modeling Data Using SQL

  • Using the MODEL clause
  • Demonstrating Cell and Range References
  • Using the CV Function
  • Using FOR Construct with IN List Operator, incremental values and Subqueries
  • Using Analytic Functions in the SQL MODEL Clause
  • Distinguishing Missing Cells from NULLs
  • Using the UPDATE, UPSERT and UPSERT ALL Options

Data Warehousing Fundamentals

    Data Warehousing, Business Intelligence, OLAP, and Data Mining

    • Data Warehouse Definition and Properties
    • 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
    • Oracle Data Mining

    Defining Data Warehouse Concepts and Terminology

    • Data Warehouse Definition and Properties
    • Data Warehouse Versus OLTP
    • Data Warehouses Versus Data Marts
    • Typical Data Warehouse Components
    • Warehouse Development Approaches
    • Data Warehousing Process Components
    • Strategy Phase Deliverables
    • Introducing the Case Study: Roy Independent School District (RISD)

    Business, Logical, Dimensional, and Physical Modeling

    • Data Warehouse Modeling Issues
    • Defining the Business Model
    • Defining the Logical Model
    • Defining the Dimensional 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’s Strategy for 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
    • Oracle’s ETL Tools: Oracle Warehouse Builder, SQL*Loader, and 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
    • 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
    • Final Tasks

    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

    Leaving a Metadata Trail

    • 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 and Choosing Metadata Tools and Techniques
    • Integrating Multiple Sets of Metadata
    • Managing Changes to Metadata

    Data Warehouse Implementation Considerations

    • Project Management
    • Requirements Specification or Definition
    • Logical, Dimensional, and Physical Data Models
    • Data Warehouse Architecture
    • ETL, Reporting, and Security Considerations
    • Metadata Management
    • Testing the Implementation and Post Implementation Change Management

    Informatica Architecture

      Informatica Power Center Client Tools

      • Repository Manager
      • Manage Folders
      • Designer
      • Source Analyzer
      • Target Designer
      • Mapping Designer
      • Workflow Manager
      • Task Developer
      • Workflow Designer
      • Workflow Monitor
      • Workflow Log
      • Session Log
      • Types of View

      Transformation Basics

      • Classification
      • Types of Ports
      • Data Types

      Types of Transformations

      Source Qualifier Transformation

      • Creating Simple Pass through Mapping
      • Apply Various Filter Conditions
      • Specify sorted ports
      • Eliminate Duplicate Values
      • Creating Custom SQL Query
      • Joining two or more tables

      Filter Transformation

      • Compare with Source Filter
      • Types of Tracing Level
      • Types of Flatfiles
      • File Import Wizard
      • Load data from Flat File to Database
      • Load data from Database to Flat File

      Sorter Transformation

      • Types of Ports
      • Multiple Sorting

      Joiner Transformation

      • Joining two heterogenouse sources
      • Types of Joins
      • Sorted input option

      Rank Transformation

      • Types of Ports
      • Rank Index
      • Rank and Dense rank

      Sequence Generator

      • cycle option
      • Usage of Reset

      Expression Transformation

      • Use of Expression
      • Usage of Variable Port
      • IIF and Decode functions

      Aggregator Transformation

      • Informatica aggregate functions
      • Sorted input option

      Router Transformation

      • Types of Groups
      • Group Conditions

      Union Transformation

      • Types of Groups

      Normalizer Transformation

      • Types of Normalizer
      • Transpose Columns to Rows
      • Default Output Ports

      Lookup Transformation

      • Connected Vs Unconnected Lookups
      • Unconnected Procedure
      • Lookup Caches

      Stored Procedure Transformation

      • Create a Sample Procedure
      • DBA Script

      Update Strategy Transformation

      • Database opertations
      • Data Driven

      Transaction control Transformation

      • Dynamic File Generation

      Slowly Growing Dimension

      Slowly changing Dimension

      • Type 1
      • Type 2
      • Type 3

      Transformation Developer

      • Create a Reusable Transformation
      • Promoting Transformations

      Mapplet Designer

      • Create a reusable Mappings

      Mapping Parameters

      • Design Parameter File

      Mapping Variables

      • Set variables function

      Session variables

      • Setting Connections
      • Workflow variables

      File Repository Concepts

      • Indirect loading

      Target Load Plan

      • Types of scheduling
      • Time-based schedule
      • Event -based schedule

      Mapping Migration Process

      • Copy from Folder
      • Import and Export

      UNIX Shell Scripting

      Unix Command Review

      • Basic Unix commands
      • General commands
      • File and directory handling commands
      • Filename generation characters
      • I/O Redirection features
      • Other commands

      Getting Started

      • What is a shell script?
      • Development guidelines
      • Creating and editing shell scripts
      • Naming and storing shell scripts
      • Executing shell scripts
      • Exercise: Write a simple shell script

      Using Variables

      • Environment variables
      • Local variables
      • Assigning values to variables
      • Assessing variable values
      • Using quotes
      • Delimiting variable names
      • Echo control sequences
      • Exercise: Add variables to a script

      Integer Arithmetic

      • Using the expr command
      • Using the (( )) notation
      • Exercise: Add integer arithmetic to a shell script

      Handling Run Time Data

      • The read command
      • Command line arguments
      • Exercise: Writing a generic shell script
      • Exercise: Writing an interactive shell script

      Condition Execution

      • The if statement
      • The test command
      • Other test notations
      • Default and substitute variables
      • Exit status codes
      • Exercise: Adding validation to previous scripts

      Loop Constructs

      • The while loop
      • The until loop
      • The for loop
      • The while true and until false loops
      • Loop control commands
      • Exercise: Enhancing the previously written scripts
      • Exercise: Writing a guess-the-number game

      Multi-Branch Decisions

      • The case statement
      • Menu driven applications
      • Exercise: Developing and writing a menu system


      • What is a function?
      • Syntax
      • Examples
      • Exercise: Add a function to a script

      Interrupt Handling

      • Interrupt signals
      • Trapping interrupts
      • Exercise: Adding traps to the menu script

      Additional Features and Facilities

      • The exec commands
      • The includes notation
      • More about loops
      • Arrays
      • Here Documents
      • Exercise: Create a here script

      Informatica Certification Training

      The Informatica Certification Program can give you a distinct advantage. An Informatica Certification demonstrates that you have a solid understanding of a job role and the Informatica products used in that role. Becoming an Informatica Certified Professional can help raise your visibility and increase your access to the industry's most challenging opportunities.

      Datawarehouse ETL Tool Training Courses in Chennai

      Informatica Training Course Highlights:

      • 1) Two days free trial - If candidate likes this course, these days are adjusted in his actual schedule.
      • 2) Live Project Exposure of Fortune companies.
      • 3) Training by Subject Matter experts from CMM Level 5 companies
      • 4) Running in two major financial cities of India – Chennai and Mumbai
      • 5) Worldwide online training of Datawarehouse and corporate classes at affordable fees.
      • 6) Our basic course worth more than the advanced course of other institutes/freelancers.
      • 7) Free Interview preparations.
      • 8) 100% free assistance for Informatica certifications.
      • 9) 100 % guarantee in succeeding the certification at affordable fees.
      • 10) Also provide online training to students of foreign countries.
      • Learn Informatica Training from the Best Datawarehouse Institute in Chennai

      Informatica Training Locations in Chennai

      Greens Technology
      15 First Street Padmanabha Nagar, Adyar, Chennai
      Tel: +91- 89399 15577
            +91- 89399 25577

      Informatica Training Reviews

      Greens Technology Reviews given by our students already completed the training with us. Please give your feedback as well if you are a student.