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Mulund West, Mumbai

Course ID: 27872

Mulund West, Mumbai

No Reviews Yet

About the Course

This course covers both theory as well as practical. The course is designed in such a way that every participant gets in depth understanding and exposure of informatica as it includes handson exercise on industry based use cases. Post completion of use cases, we focus on topics such as optimization, tuning, architecting, capacity planning and best practices. This course is exclusively designed for professionals 1-15 years of work experience.

Topics Covered

Data warehousing Concepts:
What, Why and How about Data Warehousing?
Types of OLAP
Dimension Tables and Types
Fact Tables and Types
Normalization and Denormalization
Different ways for Normalization
Ralph Kimball's way
Bill Inmon's thoughts
Best Practices
Measures and Types
Star and Snow Flake Schema
Data Warehouse Architecture
Layers in data warehouse
Overview of BI Tools
Overview of ETL Tools
SMP Database
MPP Database
Storage architecture
Hardware Specifications
Why OLAP and why not OLTP?
Different Requirements
Pros and Cons
Transaction Types
Building Approach
Slowly Changing Dimension and Types
Surrogate Keys and its importance
Dependent and Independent tables
What is junk and why?
Drill-down, Drill-up
Cube and its pros and cons
Cross Tab
Analytics and Why
What is big data?
Future Aspects
Technology v/s Tools
Thoughts v/s Implementations

Informatica Contents:
Day 1:
Informatica Training Contents
Developer Training with respect to Greenplum
Introduction and Architectural Overview
Extraction, Transformation and loading process
Informatica PowerCenter Architecture
Basic Element of Data Warehouse
• Source System
• Data Staging Area
• Facts & Dimensions
• Data warehouse and Latency
• Data Integration
Repository Topics
• Repository Server and agent
• Repository maintenance
• Repository Server Administration Console
• Security, Repository, privileges and folder permissions
• Objects sharing, searching, and locking
• Metadata extensions
Lab 1- Create a Folder
Source Object Definitions
• Source types
• Source properties
Lab 2- Analyze Source Data
Target Object Definitions
• Target types
• Target properties
Day2 :
Lab 3- Import Target Schema
Transformation Concepts
• Transformation types and views
• Transformation features and ports
• Expression transformation
• Informatica functions and data types
• Mapping components
• Source Qualifier transformation
• Pre SQL and Post SQL
• Mapping validation
• Data flow rules
• Objects export and import
Lab 4 –Create a Mapping
• Workflow Tools
• Workflow Structure and configuration
• Workflow Tasks
• Workflow Design and properties
Session Tasks
• Session Task properties
• Session components
• Transformation overrides
• Session partitions
Day3 :
Workflow Monitoring
• Workflow Monitor views
• Monitoring a Server
• Actions initiated from the workflow Monitor
• Truncating Monitor Logs
Lab 6 – Start and Monitor a Workflow
• Debugger features
• Debugger windows
• Tips for using the Debugger
Lab 7 –The Debugger
Filter transformation
• Filter properties
Lab 8- Flat File Wizard and Filter
Aggregator transformation
• Aggregation function and expressions
• Aggregator properties
• Using sorted data
• Incremental Aggregation
Joiner transformation
• Joiner types
• Joiner conditions and properties
• Joiner usage and Nested joins
Lab 9 – Heterogeneous join
Sorter transformation
• Sorter properties
• Sorter limitations
Lab 10 – Sorter
Lookup transformation
• Lookup principles
• Lookup properties
• Lookup techniques
Lab 11 – Basic Lookup
Target options
• Row type indicators
• Row loading operations
• Constraint- based loading
• Rejected row handling options
Day4 :
Lab 12 – Deleting Rows
Update Strategy transformation
• Update strategy expressions
• Smart aggregation
• Refresh strategies
Lab 13 – Data Driven Inserts and Rejects
Router transformation
• Using a router
• Router groups
Lab 14 – Router
Mapping Parameters and variables
• Mapping parameters and variables usage
• System Variables
• Variables functions
Conditional Parameters and Variables
• Mapping parameter and variable usage
• System Variables
• Variable functions
Conditional Lookups
• Usage and techniques
• Advantage
• Functionality
Lab 15 – Straight Load
Lab 16 – Conditional Lookups
Heterogeneous Targets
• Heterogeneous target types
• Target type conversions and limitations
Lab 17 – Heterogeneous Targets
• Functionality and Advantages
• Mapplet types and structure
• Mapplet limitations
Lab 18 – Mapplets
Reusable transformations
• Advantages
• Limitations
• Promoting and copying transformations
Lab 19 – Reusable transformations
Sequence Generator transformation
• Using a sequence Generator
• Sequence Generator properties
Concurrent and sequential Workflows
• Concurrent Workflows
• Sequential Workflows
• Stopping, Starting and suspending tasks and workflows
Additional Transformations
• Rank transformation
• Normalizer transformation
• Customer Transformation
• Transformation Control transformation
• Error Handling
• Overview of Error Handling Topics
Lab 20 – Error handling fatal and non Fatal
Mapping Variables
• Introduction to Mapping Variable and Parameters
• Creating Mapping Variables and Updating Variables
• Creating Parameter File and associating file to a Session
Day5 :
Performance Tuning
• Overview of System Environment
• Identifying Bottlenecks Lab 21 - Override Mapping Variable with Parameter Files
Reusable Workflow Tasks
• WorkLets
• Worklets Limitation
Lab 21 - Optimization, Architect, Tuning, Documentati on
Lab 22 - Industry Specific Case Study Hands On
Lab 23 – Greenplum Connectivity
Lab 24 – Informatica’s best practices
Lab 25 – Scheduling
Lab 26 – Informatica for Data Migration

Who should attend

This course is designed for Developer, Tester, Team Lead and architect and we assure you that after this deep dive training, you are somewhat 80-90% expert, rest comes out of experience.


Basic SQL

What you need to bring

A laptop"

Key Takeaways

Professional experienced Trainers
Industry specific case study
Course Materials

Date and Time

Not decided yet.

About the Trainer

Avg Rating





16 Years of Industry Experience in Big Data and Databases


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