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Talend Certification Training

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Reviews 4.9 (4.6k+)
Rated 4.7 out of 5

Learners : 1080

Duration :  25 Days

About Course

Talend Course Overview

Our Talend Online Training is designed to equip learners with the skills needed to design, develop, and manage powerful data integration and ETL (Extract, Transform, Load) solutions using Talend. This course covers everything from data extraction and transformation to cloud integration and big data processing. Whether you are a data engineer, ETL developer, or BI professional, this course will help you streamline data workflows, enhance data quality, and build scalable integration pipelines.

Key Topics Covered:

  • Introduction to Talend: Overview of Talend Studio, architecture, and components
  • ETL Fundamentals: Understanding data extraction, transformation, and loading processes
  • Talend Studio for Data Integration: Creating jobs, mappings, and reusable components
  • Data Transformation: Filtering, sorting, aggregating, and cleansing data using Talend tools
  • Quality & Profiling: Implementing data validation, deduplication, and enrichment
  • Database Connectivity: Integrating with Oracle, SQL Server, MySQL, and cloud databases
  • Big Data Integration: Working with Hadoop, Spark, and NoSQL databases
  • Cloud Integration: Using Talend Cloud for hybrid and SaaS-based data flows
  • Error Handling & Logging: Managing job execution, error recovery, and monitoring
  • Deployment & Scheduling: Deploying Talend jobs and automating workflows with TAC (Talend Administration Center)
  • Best Practices: Job optimization, performance tuning, and real-time data integration strategies

Who Can Enroll:

  • ETL and Data Integration Developers
  • Data Engineers and Architects
  • Business Intelligence (BI) Professionals
  • Database AdministratorsIT Professionals working with data pipelines

Course Benefits:

  • Gain hands-on experience in building and managing Talend ETL workflows
  • Learn to integrate data across cloud, on-premise, and big data systemsdata quality, governance, and transformation techniques
  • Enhance your career as a Talend Developer, Data Integration Consultant, or ETL Specialist

Talend Training Course Syllabus

Data Integration and Talend Studio
  • Data analytics
  • Operational integration
  • Execution monitoring
Getting Started with Talend Studio
  • Important concepts in Talend Open Studio for Data Integration
  • Launching Talend Open Studio for Data Integration
  • How to launch the Studio for the first time
  • How to set up a project
  • Working with different workspace directories
  • How to create a new workspace directory
  • Working with projects
  • How to create a project
  • How to import the demo project
  • How to import projects
  • How to open a project
  • How to delete a project
  • How to export a project
  • Migration tasks
  • Setting Talend Open Studio for Data Integration preferences
  • Java Interpreter path
  • External or User components
  • Exchange preferences
  • Language preferences
  • Debug and Job execution preferences
  • Designer preferences
  • Adding code by default
  • Performance preferences
  • Documentation preferences
  • Displaying special characters for schema columns
  • SQL Builder preferences
  • Schema preferences
  • Libraries preferences
  • Type conversion
  • Usage Data Collector preferences
  • Customizing project settings
  • Palette Settings
  • Version management
  • Status management
  • Job Settings
  • Stats & Logs
  • Context settings
  • Project Settings use
  • Status settings
  • Security settings
Designing a business Model
  • What is a Business Model
  • Opening or creating a Business Model
  • How to open a Business Model
  • How to create a Business Model
  • Modeling a Business Model
  • Shapes
  • Connecting shapes
  • How to comment and arrange a model
  • Business Models
  • Assigning repository elements to a Business Model Editing a Business Model
  • How to rename a Business Model
  • How to copy and paste a Business Model
  • How to move a Business Model
  • How to delete a Business Model
  • Saving a Business Model
Designing a Data Integration Job
  • What is a Job design
  • Getting started with a basic Job design
  • How to create a Job
  • How to drop components into the workspace
  • How to search components in the Palette
  • How to connect components together
  • How to drop components in the middle of a Row link
  • How to define component properties
  • How to run a Job
  • How to customize your workspace
  • Using connections
  • Connection types
  • How to define connection settings
  • Using the Metadata Manager
  • How to centralize the Metadata items
  • How to centralize contexts and variables
  • How to use the SQL Templates
  • Handling Jobs: advanced subjects
  • How to map data flows
  • How to create queries using the SQLBuilder
  • How to download/ upload Talend Community components
  • How to install external modules
  • How to launch a Job periodically
  • How to use the tPrejob and post job components
  • How to use the Use Output Stream feature
  • Handling Jobs: miscellaneous subjects
  • How to share a database connection
  • How to define the Start component
  • How to handle error icons on components or Jobs
  • How to add notes to a Job design
  • How to display the code or the outline of your Job
  • How to manage the sub job display
  • How to define options on the Job view
  • How to find components in Jobs
  • How to set default values in the schema of a component
Managing a Data Integration Job
  • Activating/Deactivating a Job or a sub-job
  • How to disable a Start component
  • How to disable a nonStart component
  • Importing/exporting items or Jobs
  • How to import items
  • How to export Jobs to an archive
  • How to export items
  • How to change context parameters in Jobs
  • Managing repository items
  • How to handle updates in repository items
  • Searching a Job in the repository
  • Managing Job versions Documenting a Job
  • How to generate HTML documentation
  • How to update the documentation on the spot
  • Handling Job execution
  • How to deploy a Job on SpagoBI server
Mapping Data Flows
  • tMap and tXMLMap interfaces
  • tMap operation
  • Setting the input flow in the Map Editor
  • Mapping variables
  • Using the expression editor
  • Mapping the Output setting Talend Open Studio
  • Setting schemas in the Map Editor
  • Solving memory limitation issues in tMap use
  • Handling Lookups
  • tXMLMap operation
  • Using the document type to create the XML tree
  • Defining the output mode
  • Editing the XML tree schema
Managing Metadata
  • Objectives
  • Setting up a DB connection
  • Step 1: General properties
  • Step 2: Connection
  • Step 3: Table upload
  • Step 4: Schema definition
  • Setting up a JDBC schema
  • Step 1: General properties
  • Step 2: Connection
  • Step 3: Table upload
  • Step 4: Schema definition
  • Setting up a SAS connection Prerequisites
  • Step 1: General properties
  • Step 2: Connection
  • Setting up a File Delimited schema
  • Step 1: General properties
  • Step 2: File upload
  • Step 3: Schema definition
  • Step 4: Final schema
  • Setting up a File Positional schema
  • Step 1: General properties
  • Step 2: Connection and file upload
  • Step 3: Schema refining
  • Step 4: Finalizing the end schema
  • Setting up a File Regex schema
  • Step 1: General properties
  • Step 2: File upload
  • Step 3: Schema definition
  • Step 4: Finalizing the end schema
  • Setting up an XML file schema
  • Setting up an XML schema for an input file
  • Setting up an XML schema for an output file
  • Setting up a File Excel schema
  • Step 1: General properties
  • Step 2: File upload
  • Step 3: Schema refining
  • Step 4: Finalizing the end schema
  • Setting up a File LDIF schema
  • Step 1: General properties
  • Step 2: File upload
  • Step 3: Schema definition
  • Step 4: Finalizing the end schema
  • Setting up an LDAP schema
  • Step 1: General properties
  • Step 2: Server connection
  • Step 3: Authentication and DN fetching
  • Step 4: Schema definition
  • Step 5: Finalizing the end schema
  • Setting up a Salesforce connection
  • Step 1: General properties
  • Step 2: Connection to a Salesforce account
  • Step 3: Retrieving Salesforce modules
  • Step 4: Retrieving Salesforce schemas
  • Step 5: Finalizing the end schema
  • Setting up a Generic schema
  • Step 1: General properties
  • Step 2: Schema definition
  • Setting up an MDM connection
  • Step 1: Setting up the connection
  • Step 2: Defining MDM schema
  • Setting up a Web Service schema
  • Setting up a simple schema
  • Setting up an FTP connection
  • Step 1: General properties
  • Step 2: Connection
Managing Data Routines
  • What are routines
  • Accessing the System Routine
  • Customizing the system routines
  • Managing user routines
  • How to create user routines
  • How to edit user routines
  • How to edit user routine libraries
  • Calling a routine from a Job
  • Use case: Creating a file for the current date
Using SQL Templates
  • What is ELT
  • Introducing Talend SQL templates
  • Managing Talend SQL templates
  • Types of system SQL templates
  • How to access a system SQL template
  • How to create user-defined SQL templates
  • A use case of system SQL Templates
Data Warehousing Concepts
  • ETL Concepts
  • tsortrow
  • tunite
  • tuniqerow
  • tbufferinput
  • tbuffer output
  • thashinput
  • thashoutput
  • tfilelist
  • tsleep
  • tloop
  • file input output components
  • database input output components
  • tsendmail
  • treplicate
  • tfiltercolumns
  • tfilterrows
  • treplace
  • tconverttype
  • tdie
  • tcontextload
  • tmemorizerow
  • trowgenerator
  • trunjob
  • prejob
  • postjob
  • tsamplerows
  • tnormalize
  • tdenormalize
  • tmap
  • taggrigator
  • tjoin
  • tsystem
  • Dynamic
  • tjava
  • tjavaro
  • tjavaflex
  • tschemacompliancecheck
  • tlogrow
  • tlogcatcher
  • t ststcatcher
  • tparallelize
  • tsendmai
  • tfilecopy
  • tfilearchive
  • tfileProperties
  • tfileunarchive
  • tfiletouch
  • tfiledelete
  • tfileexist
  • tfiletouch
  • tfilecopy
  • tftpfilelist
  • tftpput
  • tftpget
  • tftpdelete
  • tftpfileexist
  • tftpConnection
  • tftpRename
  • tftpfileproperties
  • toracleInput
  • toraclerow
  • toracleoutpt
  • toracleconnection
  • toracleBulk
  • toracleBulkexec
  • toracleClose
  • toracleRollback
  • toraclecommit
  • tmssqlInput
  • tmssqlrow
  • tmssqloutpt
  • tmssqlconnection
  • tmssqlBulk
  • tmssqlBulkexec
  • tmssqlClose
  • tmssqlRollback
  • tmssqlcommit
  • tDb2Input
  • tDb2row
  • tDb2outpt
  • tDb2connection
  • tDb2Bulk
  • tDb2Bulkexec
  • tDb2Close
  • tDb2Rollback
  • tDb2commit
  • OnsubJobOK
  • OnSubjobError
  • OnComponentOk
  • OnComponentError
  • runif
  • tExcelInput
  • tExceloutput
  • tfileInputdelimited
  • tfileoutputDelimited
  • tfileInputXml
  • tfileoutputXml
  • tfileinputPositional
  • tfileOutputPositional
  • SCD1
  • SCD2
  • SCD3
  • stage loading
  • Dimension Loading
  • fact Loading
  • project Explanation
Talend Course Key Features

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Talend Online Training FAQ'S

What is Talend, and why is it used?

Talend is an open-source ETL and data integration tool used to extract, transform, and load data from multiple sources. It helps businesses with data migration, data warehousing, cloud integration, and big data processing.

What are Talend Components?

Talend components are pre-built tools used in job designs to perform specific functions such as data input, transformation, output, and monitoring. Examples include tMap, tJoin, tFilter, and tLogRow.

What is the difference between Talend Open Studio and Talend Enterprise?
  • Talend Open Studio: Free, open-source version with basic ETL features.
  • Talend Enterprise: Paid version with advanced features like team collaboration, real-time processing, scheduling, and enterprise support.
What is tMap in Talend?

tMap is one of the most widely used Talend components. It allows users to perform data transformation, filtering, mapping, and joining between multiple data flows in a job.

What are the advantages of using Talend?

  • Open-source and cost-effective
  • User-friendly drag-and-drop interface
  • Scalable for big data and cloud integration
  • Supports multiple data sources (databases, flat files, APIs)
  • Includes data quality and master data management tools

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