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- What is ETL?
- Need for ETL
- ETL Glossary
- The ETL Process
- Data Extraction and Preparation
- Data Cleansing
- Data Transformation
- Data Load
- Data Refresh Strategies
- ETL Solution Options
- Characteristics of ETL Tools
- Types of ETL Tools
- ETL Tool - selection criteria
- Key tools in the market
- What is Data Warehousing?
- Using Data Warehouse Information
- Integrating Heterogeneous Databases
- Functions of Data Warehouse Tools and Utilities
- OLAP vs OLTP
- Star Schema
- Snowflake Schema
- Schema Definition
- Why Do We Need a Data Mart?
- Difficulties in Data Warehouse Tuning
- Whats Is ETL/Concepts Informatica Basics
- Informatica Intelligent Cloud Services (IICS) as an iPaaS solution
- Informatica Cloud Terminologies
- Informatica Cloud Architecture
- CDI Assets
- CDI Components
- Lab: Navigating the IICS interface
- Runtime Environments
- Secure Agent Architecture
- IICS Log Files
- Connections
- Connection Types
- Creating Connections
- Lab: Installing Secure Agent
- Lab: Creating a Salesforce connection -- Basic
- Lab: Creating a Flat File connection
- Lab: Creating a AWS Redshift/S3 connection/Athena
- Lab: Creating an Oracle connection
- Synchronization Task Overview
- Synchronization Task – Definition Step
- Synchronization Task – Source Step
- Synchronization Task – Target Step
- Synchronization Task – Data Filters Step
- Synchronization Task – Field Mapping Step
- Synchronization Task – Schedule Step
- Activity Monitor
- Lab: Creating a Synchronization Task
- Lab: Using Filter, Expression and Lookup in a Synchronization Task
- Cloud Mapping Designer Overview
- Mapping Designer Terminologies
- CLAIRE Transformation Recommendations
- Mapping Data Preview
- Field Rules
- Best Practices for Creating Mappings
- Data flow run order
- Mapping Task
- Deploy mapping updates
- Note: Components / Maplets and taskflow
- Source Transformation
- Target Transformation
- Filter Transformation
- Joiner Transformation
- Expression Transformation
- Lookup Transformation
- Union Transformation
- Mapplets
- SQL Transformation
- Aggregator Transformation
- Normalizer Transformation
- Rank Transformation
- Sequence Generator Transformation
- Java Transformation
- Lab: Using Query in a Mapping
- Lab: Using Normalizer, Aggregator, and Rank transformations in a mapping
- Lab: Using Unconnected Lookup transformation in a mapping
- Lab: Using Mapplet transformation in a mapping
- Note: All Param files on S3 and use it.
- Parameterization use cases
- Adding Parameters to a Mapping
- Creating parameters
- Parameter Types
- Using parameter files
- Parameter Best Practices
- Lab: Performing Complete Parameterization
- Lab: Using Parameter File in a Mapping task
- Lab: Using In-Out parameters for incremental data loading
- Expression Macro
- Dynamic Linking
- Lab: Using Expression Macro in a mapping
- Lab: Using Dynamic Linking in a mapping
- Replication Task Overview
- Replication Task Features
- Replication Task: Source and Target Options
- Other Replication Task Options
- Resetting the Target Table
- Generating Non-Unique Index
- Lab: Create a Replication Task
- Masking Task Overview
- Masking Task: Source and Target Options
- Data Subset: Row Limits and Data Filters
- Field Masking Rules
- Masking Rule Types
- Refresh Masking Task metadata
- Reset a Masking Task
- Masking Best Practices
- Lab: Create Masking task
- Mass Ingestion Task Overview
- Functionalities
- Configuring a Mass Ingestion Task
- Creating a Mass Ingestion Task
- Task flow overview
- Linear Taskflows
- File Listener Enhancements
- Taskflow Steps
- Taskflow Templates
- Using REST APIs
- Invoke a Taskflow through a File Listener
- Lab: Passing in-out parameters in a Taskflow
- Lab: Invoking a Taskflow through a File Listener
- Web Service transformation
- REST V2 Connector
- Hierarchical Schemas
- Hierarchy Parser Transformation
- Hierarchy Builder Transformation
- Lab: Creating a mapping using a REST V2 connector
- Lab: Using Web Services transformation in a mapping
- Lab: Using Hierarchy Parser and Hierarchy Builder Transformation
- Intelligent Structure Model
- Intelligent Structure Discovery Process
- Intelligent Structure Example
- Refining a Discovered Structure
- Editing an Intelligent Structure Model
- Using intelligent structure models in Structure Parser transformation
- Lab: Creating an Intelligent Structure Model
- Lab: Using Structure Parser transformation in a mapping
- Primary Key Chunking
- Lookup SQL Override
- Partitions Overview
- Types of Partitions
- Partitioning Rules and Guidelines
- Pushdown optimization overview
- Types of pushdown optimization
- Cross-schema pushdown optimization
- Pushdown optimization user-defined parameters
- Pushdown compatible connections
- Secure agent groups
- Secure agent groups with multiple agents
- Shared secure agent groups
- DTM performance properties
- Types of exceptions
- User-defined exceptions
- Non-fatal exceptions
- Default Field Value Setting
- Row Error Logging
- Error handling settings
- Fatal exceptions
- Bad files or Reject files
- Lab: Creating a mapping to handle non-fatal errors
- Licenses
- Administrator Service
- User Roles (System-defined Roles and Custom Roles)
- Creating a User
- User Groups
- Permissions
- Object-Level Permissions
- Organization Hierarchy
- Sub-Organization
- Importing and Exporting Assets
- Asset Dependency
- Add-on Bundles
- Lab: Configure Administrative settings for your Informatica Cloud org
- Schedules
- Schedule Repeat Frequency
- Schedule Blackout Period
- Schedule Export
- Monitoring tasks
- Email Notifications
- Event Monitoring
- Lab: Creating a schedule
- Discuss Informatica Discovery IQ
- List the features of Discovery IQ
- Exploring Discovery IQ features
- Rest Client: PostMan
- Senario Based Practicals
- CDC
- SCD1/SCD2/SCD3
