Mapping may be a collection of source and target objects which is engaged together through a group of transformations. These transformations are formed with a group of rules that outline how the data is loaded into the targets and flow of the data.

Mapping in Informatica includes the subsequent set of objects, such as:

Source definition: The source definition defines the structure and characteristics of the source, like basic data types, sort of the data source, and more.
Transformation: It defines how the source data is modified , and various functions are often applied during this process.
Target Definition: The target definition defines where the data are going to be loaded finally.
Links: Link is employed to connecting the source definition with target tables and different transformations. And it shows the flow of knowledge between the source and target.

Why can we need Mapping?

In Informatica, Mapping is an object which may define the method of modification of the source data before it reaches the target object.

For example: Suppose an employee name as “Edward Cullen” within the source system and therefore the target system. Now we’d like to possess an employee name within the “Edward Cullen” format. At the mapping level, these sorts of operations are designed.

Mapping can define the data transformation details and source or target object characteristics because it’s a primary object within the Informatica.

Mappings define the data transformation for every row at the individual column levels. and that we can hold multiple sources and targets during a single mapping.

Components of Mapping

Here are some essential elements utilized in mapping, such as:

Source tables
Mapping parameters and variables
Target objects
Mapping transformations

A mapping contains sources, targets, mapping parameters, variables, multiple changes, mapplets, and user-defined functions.

Mapping Source: Mapping sources are those objects whose allow fetching the source data. It are often a file , database table, COBOL file source, or XML source.
Mapping target: The mapping target is that the destination objects where the ultimate data is loaded. A mapping target are often a relational table of a database, XML file, or a flat-file. Sources and targets must be present in any mapping with their different data types.
Mapping Parameters and Variables: it’s an optional user-defined data types. The Mapping parameters and variables are wont to create temporary variable objects. It helps us to define and store temporary values during the processing of mapping data. This user-defined data type is meant for mapping.
Mapplets: The mapplets are objects which contains a group of source, transformation, or targets. With the assistance of Mapplets, we will reuse the prevailing functionality of a group of changes.

What is Stage Mapping?

In a stage mapping, we create the replica of the source table.

For Example, if we’ve a “Student” table, and that we want to make a uniform table, “Student_stage” in ETL schema.

A local stage table provides some advantages, like production downtime, so it’ll not affect the ETL system because we’ve our own “Student_stage” table rather than pertaining to the “Student” table. There are often another operations and processes which may affect the performance. The ETL processes will only access it once we have a reproduction staging table. Then it provides advantages with better performance.

In Stage Mappings,

Source and Target tables are having identical structures.
In the staging table, data may be a replica of source table data.
In the source table, data may be a subset of source data.

For example, if the source table contains student details of rollno 1, 2, 3, and 10. The stage table may be a quite table which has student records of rollno 1 & 3 only.

In the data warehouse, we’d like to form stage tables to make the method of knowledge transformation efficiently, to attenuate the dependency of ETL or Data Warehouse from the real-time OS . It could happen once we are fetching the relevant data only.

Mapping Parameters and Variables

Informatica features a way of defining parameters and variables as other programming languages. But Informatica isn’t a code-based language a bit like other programming languages.

In Informatica, we’d like to follow the predefined syntax and navigation to make parameters and variables.

Here are some fundamental differences between the mapping parameters and mapping variables, such as:

Mapping Parameters

Mapping Variables

Mapping parameters are those data types whose value assigned directly and remains constant throughout the execution of the mapping.

For example: If we’ve created a mapping parameter rollno=2, then the worth 2 are going to be constant throughout the entire execution of mapping.

The referenced parameter will always return value 2 for that instance of mapping run. and therefore, the value of a parameter is often redefined for a replacement mapping instance.

Mapping variables are the objects referenced throughout the execution of the mapping, and their values are often reassigned.

For example, A mapping variable of total_marks is employed in mapping, and its value are going to be updated on the idea of marks.

So, this brings us to the end of blog. This Tecklearn ‘Mapping in Informatica’ blog helps you with commonly asked questions if you are looking out for a job in Informatica. If you wish to learn Informatica and build a career in Datawarehouse and ETL domain, then check out our interactive, Informatica Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:

https://www.tecklearn.com/course/informatica-training-and-certification/

Informatica Training

About the Course

Tecklearn’s Informatica Training will help you master Data Integration concepts such as ETL and Data Mining using Informatica PowerCenter. It will also make you proficient in Advanced Transformations, Informatica Architecture, Data Migration, Performance Tuning, Installation & Configuration of Informatica PowerCenter. You will get trained in Workflow Informatica, data warehousing, Repository Management and other processes.

Why Should you take Informatica Training?

Informatica professionals earn up to $130,000 per year – Indeed.com
GE, eBay, PayPal, FedEx, EMC, Siemens, BNY Mellon & other top Fortune 500 companies use Informatica.
Key advantages of Informatica PowerCenter: Excellent GUI interfaces for Administration, ETL Design, Job Scheduling, Session monitoring, Debugging, etc.

What you will Learn in this Course?

Informatica PowerCenter 10 – An Overview

Informatica & Informatica Product Suite
Informatica PowerCenter as ETL Tool
Informatica PowerCenter Architecture
Component-based development techniques

Data Integration and Data Warehousing Fundamentals

Data Integration Concepts
Data Profile and Data Quality Management
ETL and ETL architecture
Brief on Data Warehousing

Informatica Installation and Configuration

Configuring the Informatica tool
How to install the Informatica operational administration activities and integration services

Informatica PowerCenter Transformations

Visualize PowerCenter Client Tools
Data Flow
Create and Execute Mapping
Transformations and their usage
Hands On

Informatica PowerCenter Tasks & Workflows

Informatica PowerCenter Workflow Manager
Reusability and Scheduling in Workflow Manager
Workflow Task and job handling
Flow within a Workflow
Components of Workflow Monitor

Advanced Transformations

Look Up Transformation
Active and Passive Transformation
Joiner Transformation
Types of Caches
Hands On

More Advanced Transformations – SQL (Pre-SQL and Post-SQL)

Load Types – Bulk, Normal
Reusable and Non-Reusable Sessions
Categories for Transformation
Various Types of Transformation – Filter, Expression, Update Strategy, Sorter, Router, XML, HTTP, Transaction Control

Various Types of Transformation – Rank, Union, Stored Procedure

Error Handling and Recovery in Informatica
High Availability and Failover in Informatica
Best Practices in Informatica
Debugger
Performance Tuning

Performance Tuning, Design Principles & Caches

Performance Tuning Methodology
Mapping design tips & tricks
Caching & Memory Optimization
Partition & Pushdown Optimization
Design Principles & Best Practices

Informatica PowerCenter Repository Management

Repository Manager tool (functionalities, create and delete, migrate components)
PowerCenter Repository Maintenance

Informatica Administration & Security

Features of PowerCenter 10
Overview of the PowerCenter Administration Console
Integration and repository service properties
Services in the Administration Console (services, handle locks)
Users and groups

Command Line Utilities

Infacmd, infasetup, pmcmd, pmrep
Automate tasks via command-line programs

More Advanced Transformations – XML

Java Transformation
HTTP Transformation

Got a question for us? Please mention it in the comments section and we will get back to you.

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