ETL Training
Introduction to ETL
Learn the fundamentals of ETL (Extract, Transform, Load) processes and their importance in data management. Understand how ETL fits into data warehousing and business intelligence.
ETL Tools and Technologies
Explore various ETL tools and technologies used in the industry. Learn about popular ETL tools such as Informatica, Talend, Apache Nifi, and Microsoft SSIS.
Data Extraction Techniques
Study techniques for extracting data from different sources. Learn how to connect to various databases, APIs, and flat files to extract data efficiently.
Data Transformation and Cleaning
Understand the process of transforming and cleaning data to make it suitable for analysis. Learn about data cleansing, normalization, and aggregation techniques.
Data Loading Strategies
Learn about different strategies for loading data into target systems. Understand full load, incremental load, and CDC (Change Data Capture) methods.
Performance Optimization in ETL
Explore techniques to optimize ETL processes for better performance. Learn about parallel processing, memory management, and optimizing SQL queries.
ETL Testing and Validation
Study methods for testing and validating ETL processes. Learn how to ensure data quality, integrity, and consistency through various testing strategies.
Data Warehousing Concepts
Understand the role of ETL in data warehousing. Learn about data warehouse architecture, star and snowflake schemas, and the importance of ETL in building data warehouses.
ETL Best Practices
Familiarize yourself with best practices for designing and implementing ETL processes. Learn about data governance, error handling, and maintaining ETL pipelines.
Real-world ETL Scenarios
Engage in real-world ETL scenarios to apply your knowledge. Work on projects involving data migration, integration, and data warehousing using ETL tools.
Advanced ETL Techniques
Dive into advanced ETL techniques, such as real-time ETL, ETL for big data, and cloud-based ETL solutions. Learn how to handle complex transformations and large data volumes.
ETL Syllabus
- DWH Data Warehousing Concepts
- What is Data Warehouse?
- Need of Data Warehouse
- Introduction to OLTP, ETL, and OLAP Systems
- Difference between OLTP and OLAP
- Data Warehouse Architecture
- Data Marts
- ODS [Operational Data Store]
- Dimensional Modelling
- Difference between Relational and Dimensional Modelling
- Star Schema and Snowflake Schema
- What is Fact Table?
- What is Dimension Table?
- Normalization and De-Normalization
- ETL Testing
- ETL Architecture
- What is ETL and the Importance of ETL Testing
- How DWH ETL Testing is Different from Application Testing
- SDLC/STLC in the ETL Projects (e.g., V Model, Waterfall Model)
- Challenges in DWH ETL Testing Compared to Other Testing
- Incompatible and Duplicate Data
- Loss of Data During ETL Process
- Testers Have No Privileges to Execute ETL Jobs by Their Own
- Volume and Complexity of Data is Very Huge
- Fault in Business Process and Procedures
- Trouble Acquiring and Building Test Data
- ETL Testing Workflow Activities Involved
- Analyze and Interpret Business Requirements/Workflows to Create Estimations
- Approve Requirements and Prepare the Test Plan for System Testing
- Prepare Test Cases with the Help of Design Documents Provided by the Developer Team
- Execute System Testing and Integration Testing
- Best Practices to Create Quality Documentations (Test Plans, Test Scripts, and Test Closure Summaries)
- How to Detect Bugs in ETL Testing
- How to Report Bugs in ETL Testing
- How to Coordinate with Developer Team for Resolving Defects
- Types of ETL Testing
- Data Completeness
- Data Transformation
- Data Quality
- Performance and Scalability
- Integration Testing
- User-Acceptance Testing
- SQL Queries for ETL Testing
- Incremental Load Testing
- Initial Load / Full Load Testing
- Different ETL Tools Available in the Market
- Informatica
- Ab Initio
- IBM Data Stage
- Power Center Components
- Designer
- Repository Manager
- Workflow Manager
- Workflow Monitor
- Power Center Admin Console
- Informatica Concepts and Overview
- Informatica Architecture
- Sources
- Working with Relational Sources
- Working with Flat Files
- Targets
- Working with Relational Targets
- Working with Flat File Targets
- Transformations – Active and Passive Transformations
- Expression
- Lookup – Different Types of Lookup Caches
- Sequence Generator
- Filter
- Joiner
- Sorter
- Rank
- Router
- Aggregator
- Source Qualifier
- Update Strategy
- Normalizer
- Union
- Stored Procedure
- Slowly Changing Dimension
- SCD Type1
- SCD Type2 — Date, Flag, and Version
- SCD Type3
- Workflow Manager
- Creating Reusable Tasks
- Workflows, Worklets & Sessions
- Tasks
- Indirect Loading
- Constraint-Based Load Ordering
- Target Load Plan
- Worklet, Mapplet, Reusable Transformation
- Migration - XML Migration and Folder Copy
- Scheduling Workflow
- Parameter and Variables
- XML Source, Target, and Transformations
- Performance Tuning
- Pipeline Partition
- Dynamic Partition
- Pushdown Optimization
- Preparation of Test Cases
- Executing Test Cases
- Preparing Sample Data
- Data Validation in Source and Target
- Load and Performance Testing
- Unit Testing Procedures
- Error Handling Procedures
Training
Basic Level Training
Duration : 1 Month
Advanced Level Training
Duration : 1 Month
Project Level Training
Duration : 1 Month
Total Training Period
Duration : 3 Months
Course Mode :
Available Online / Offline
Course Fees :
Please contact the office for details