Talend Course Content
Data Modeling Concepts
Understanding the basics of Data Modeling, its significance and how to deploy Data Modeling in Data Warehouse environment.
Deep Dive into Data Modeling
The various types of Data Modeling, learning to perform Conceptual Data Modeling, Physical Data Modeling, Logical Data Modeling, understanding the scope and benefits of Data Modeling.
Multidimensional Data Modeling
The basic Architecture of multidimensional modeling, deploying Cubes to perform multidimensional modeling, understanding the concepts of Facts and Dimensions and the differences between the two.
Introduction to Talend
The Talend Open Source data integration tool, working with Big Data, understanding the Talend Open Studio.
Understanding the installation of Talend, system requirements, troubleshooting of common errors and issues related to installation.
Talend Key Features
Learning about the Talend Architecture, important concepts and features, Talend components like Job, Workspace, Metadata, Project, etc.
Talend Job Creation
Learning to create a Talend Job, working with Delimited file, working with Meta Data, schema for data integration, understanding Propagation, deploying of tFilterRow and string filter for creating Jobs, creation of CSV file.
Data Management Techniques
Deploying Talend Open Studio for Data Management, data quality, integration, understanding the ETL and Data Warehousing concepts.
Schema & Data Aggregation
Detailed understanding of Talend Job design, it features, learning about tMap, data aggregation techniques, tReplicate for performing different operations on a Schema, tMap for mapping input and output data.
Working with DataSource Connection, deploying in database component, creating a connection, database source and target, metadata and schema importing.
Introduction to Talend Functions, calling and deploying the Functions, understanding Routines, Talend Open Studio for XML data processing, date format function.
Transforming Data, Running the Job, Combining Columns, Duplicating a Job
Working with Metadata
Creating Metadata, Joining Data Sources.
Capturing Rejects, Correcting the Lookup, Duplicating a Job
Filtering Output Data, Using Multiple Filters.
Using Context Variables from Talend Job, Repository as Metadata.
Graphical Interface of Talend
Building Jobs, Graphical Jobs, Graphical Interface Of Talend, Talendâ€™s Components Naming Convention
Row â€“ Main Connection, Row â€“ Iterate Connection, Trigger â€“ On sub Job ok Connection, Trigger â€“ On Component OK Connection
File Management in Talend
Connecting Talend with Hadoop
Deploying Talend to work with Hadoop, defining the ETL method, Hive implementation with Talend, importing data in Hive, Hive partitioning, Pig in Talend, data loading and parallel data execution.
Project â€“ Creating Jobs using Metadata and using transformation stepsTopics â€“ This project is involved with deploying metadata for creating a Talend job. Some of the steps involved are building various files like delimited, XML, and Excel, coming up with a database connection, deploying metadata, data integration schema, learning about propagation, working with tFilterRow for filtering rows on certain conditions on columns, creation of CSV files, and designing a Talend job.