Informatica ETL Tools

This is a online course is to gain comprehensive understanding of Informatica 9.6.1. The aim is to learn essential concepts in Informatica 9.6.1 right from scratch. The tutorials will help you learn about Introduction to Datawarehousing and ETL, Mapping, Workflow, Introduction Of Transformation, Expression, Filter, Router, Sorter, Aggregator, RANK Transformation, Unconnected and Connected Lookup, Joiner, Update Strategy, Connection Explorer.

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 3h 36m | 33 Videos | 89102 Views |   All Levels

What is Informatica 9.6.1

Informatica is a widely used ETL tool which is used to extract the raw data and load it into the target data after making some transformations. ETL stands for Extract Transform Load which refers to the processes performed when transforming raw data to a data warehouse or data mart or relational databases. Informatica is an easy to use tool and it also has a simple visual interface like forms.

Why Informatica is Successful

Informatics tool is successful because of the following reasons

• Informatica enables lean integration
• It has a high rate successful deployment
• Informatica offers easy training and tool availability
• It is a less expensive tool when compared to other ETL tools
• Informatica has an internal scheduler which other ETL tools do not have

Informatica 9.6.1 Course Objectives

After the completion of this course you will be able to

• Have a clear understanding of Informatica, its architecture and the components
• Use Informatica components to build Mappings, Tasks and workflows
• Understand workflow task and job handling
• Perform troubleshooting, error handling and recovery
• Use Informatica Powercenter ETL tool in real time projects
• Implement performance tuning using Informatica

Pre requisites

The pre requisites for taking this course includes basic knowledge of SQL and basic Unix. People who are also very keen to learn about Informatica ETL tool can also take up this course.

Target Audience

The following persons can take up this course

• Software developers
• Analytics professionals
• ETL or Data warehouse professionals
• Graduates who wanted to enter IT field
• Mainframe developers and architects

Informatica 9.6.1 Course Description

Section 1: Introduction

Introduction to Data warehousing and ETL

The data in a data warehouse system is loaded through an ETL tool. Defining an ETL process plays an important role in designing the data warehouse. The speed and reliability of ETL operations are the basis of the data warehouse. This section includes the following topics

• What is a data warehouse ?
• Data warehouse tasks
• Data warehouse architectures
• Why do you need ETL
• What does ETL accomplish
• ETL process – Roles and responsibilities

Introduction and Usage of PC Express of 9.6.1

Powercenter Express is used to design and implement the data integration solutions. Powercenter express includes application clients, repositories and application services. This section includes

• Powercenter Express Overview
• Powercenter Express Architecture – where the components are explained in detail
• Powercenter Express example

Data Viewing And Profiling

Powercenter express is used to complete the data integration solutions. The developer tool and administration tool helps to do that. This chapter contains step by step procedure for data integration process.

Section 2: Mapping

Mapping

A mapping is a set of inputs and outputs that represents the data flow between sources and targets. If a mapping is run it uses the instructions configured in the mapping to read, transform and write data. This chapter contains an overview of mapping.

Create and Run the Mapping

In this section you will learn how to create a mapping, add a transformation to the mapping, add a target to the mapping and how to run the mapping and review the results. All these are explained in a step by step procedure using few screenshots for your easy understanding.

Section 3: Workflow

Workflow Introduction

Workflow is a graphical representation of a set of events, tasks and decisions that define a business process. In this lesson you will learn about reviewing the mapping using joiner transformation to join data from two file sources.

Create and Deploy Workflow

This chapter lets you learn how to create a workflow, deploy and run the workflow in Powercenter Express using few screenshots.

Section 4: Introduction of Transformation

Introduction of Transformation

A transformation is an object that generates, modifies or passes data. There are a set of transformations in Informatica 9.6.1 to perform specific functions. Transformations can be active or passive. They can either be connected or unconnected to the data flow. The different type of transformations along with its type and description are explained in this section in brief.

Section 5: Expression Transformation

Expression Transformation

The expression transformation is passive or connected type. It performs a calculation based on values within a single row. This section also gives you an example of expression transformation.

Section 6: Filter Transformation

Filter Transformation

Filter transformation specifies a condition used to filter rows passed through this transformation. The return value of filter transformation gives either True or False based on whether a particular row meets the specified condition or not. This chapter also gives you example of Filter transformation.

Section 7: Router Transformation

Router Transformation

This transformation routes data into multiple transformations based on a group expression. The return value of router transformation is either true or false based on whether the row meets the specified group expression. An example is given to explain this transformation.

Section 8: Sorter Transformation

Sorter Transformation

This is an active and connected transformation used to sort the data from relational or flat file sources. The sorting can be done either in ascending or descending order using the sort key. Sorter transformation can also be used for case sensitive sorting. This chapter includes

• Procedure to create sorter transformation
• Configuration of sorter transformation
• Performance improvement tip
• Example of sorter transformation

Section 9: Aggregator Transformation

Aggregator transformation

Aggregator transformation is an active transformation used to perform calculations on groups of data. The aggregator transformation has more benefits than SQL and conditional clauses can be used in this transformation to filter rows. This section covers the following topics

• Steps to create an aggregator transformation
• Configuration of the components in Aggregator transformation
• Properties of aggregator transformation and its description –
• Aggregate expressions
• Nested aggregate functions
• Incremental aggregation

Use of Aggregator Transformation

This section explains the use of aggregator transformation to calculate sums, averages, counts and other operations on group of data. It also explains the use of conditional clause in aggregator transformation with example.

Section 10: RANK Transformation

RANK Transformation

Rank transformation is an active and connected transformation used to filter the data based on group and ranks. It is used to select the smallest or largest string value. This section gives a brief overview of rank transformation, steps in creating a rank transformation, configuring rank transformation and examples of rank transformation. The sessions are explained using screenshots for easy understanding.

Section 11: Unconnected Lookup

Introduction of Lookup Transformation

Lookup is an passive or active transformation and can be used in connected or unconnected mode. This transformation is used to look up data in a flat file, relational table, view or synonym. It will return a single or multiple rows. The lookup transformation is used to perform calculation, get a related value, get multiple values and update slowly changing dimension tables. The different type of lookup transformation are explained in detail under this section

• Flat file or relational lookup
• Pipeline lookup
• Connected or Unconnected lookup
• Cached or Uncached lookup

Creation of unconnected Lookup Transformation

Unconnected lookup can be used when you require only one column from the lookup table. An unconnected lookup is not connected to any source or any other transformation. This section lets you learn the step by step procedure to create the unconnected lookup transformation. An example for unconnected lookup transformation is also given under this chapter.

Section 12: Connected Lookup

Introduction of connected Look up Transformation

A connected lookup receives source data, undergoes a lookup and returns data to the pipeline. It receives input values directly from the pipeline. It gives multiple output values to another transformation. Connected lookup transformation supports user defined default values. This chapter gives a detailed introduction to connected lookup transformation and tells you how it is different from unconnected lookup transformation

Section 13: Joiner

Introduction and creation of joiner Transformation

Joiner transformation is an active and connected transformation which is used to join two heterogeneous sources. This transformation joins sources based on a condition that matches between the two sources. This chapter includes the steps to create a joiner transformation, configuration of the properties of joiner transformation, Join condition and Join types. You will also learn the reason why joint transformation is known as blocking transformation and the limitations of joiner transformation.

Section 14: Update Strategy

Introduction to update strategy transformation

Update strategy transformation is used to insert, update and delete records in the target table. When a target table is designed you should decide which data should be stored in the target. The topics included in this section are

• Two levels of update strategy – Session level and Mapping level
• Flagging rows in mapping with update strategy
• Update strategy expression
• Update strategy and Lookup transformation
• Update strategy and Aggregator transformation
• Example of Update strategy transformation

Section 15: Recap of all Transformations

Recap of all Transformations

This section gives you a quick overview of all the types of transformation and it includes the type, description, expression and the return value of each transformation in a table format.

Section 16: Connection Explorer

Creation database connection

The connection explorer view is used to create relational or non relational data objects and to view relational or non relational database connections. The database connection can be done using the Create Connection button in the Connection Explorer view. This chapter has the following sections under it

• Creating connection
• Showing connections
• Steps to edit a connection
• Steps to copy a connection
• Steps to delete a connection
• Refreshing the connections list

Expression Transformation Database

Expression transformation is used for row wise calculation of values. The examples include concatenating the first and last name, adjusting the salary, etc. This transformation can also be used to test conditional statements before it is being passed on to other transformation. This tutorial includes how to create expression transformation, adding expressions, expression transformation tabs, configuring ports and expression transformation examples.

Section 17: Router Transformation Using Database

Router Transformation

Router transformation is used to test a condition and filter the data. It is very similar to filter transformation. It differs only in few aspects like in filter transformation you can specify only one condition whereas in router transformation you can specify more than one condition. So in router transformation the same data can be tested under multiple conditions. In this chapter we will see the steps to create a router transformation, configuration of router transformation for different groups and router transformation examples.

Filter database

In this section you will learn about filter transformation, its creation and configuration. You will also learn about the advantages using filter transformation over router transformation using examples.

FAQ’s General Questions

• Why should I learn Informatica ?

Informatica 9.6.1 offers the leading data integration platform. This data integration platform works with wide range of disparate standards, systems and applications. This feature makes Informatica unique among all the other today’s data integration platforms. Companies who needs to solve data integration are issues are going in for Informatica- and this has increased the demand for people who are knowledgeable  in Informatica. Due to the demand for Informatica experts the salary of such professionals are also high. Thus you can have a great career by choosing this course on Informatica.

Testimonials

Hassina

It was a wonderful experience learning from educba. This course provided complete details about Informatica 9.6.1 and its concepts. It covers all the important concepts of Informatica and so once you have completed this course you can start working with Informatica directly at your workplace like an expert. Real time examples are provided for each concept to make the learning and understanding easy. Quality course at a great cost. Definitely recommended.

Jason

This tutorial is amazing and helpful as it covers all the relevant content of the course topic in a proper way. It helped me to gain a lot of knowledge about Informatica 9.6.1. The content of the course was very well structured and explained neatly. I am really satisfied with this course.

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