Who should attend
QA testers, data testers, BI analysts and professionals validating data warehouse or migration pipelines.
Prerequisites
Basic SQL is recommended. Database fundamentals can be taught as a prerequisite module.
Learning outcomes
- Explain ETL/ELT architecture and data warehouse concepts.
- Translate mapping and transformation rules into test scenarios.
- Perform source-to-target, completeness and reconciliation checks.
- Validate transformations, incremental loads and slowly changing dimensions.
- Test data quality, error handling and restart/recovery behaviour.
- Report data defects with reproducible SQL and sample evidence.
Detailed curriculum
8 modules01Data warehousing and ETL foundations
- Operational systems, staging, ODS, data warehouse and data marts
- ETL versus ELT and batch versus streaming concepts
- Fact and dimension tables; star and snowflake schemas
- Full load, incremental load and CDC concepts
- Data pipeline components and typical failure points
02Requirement and mapping analysis
- Understanding BRD, source-to-target mapping and transformation specifications
- Source/target profiling and data type/length/precision review
- Business rules, default values, lookup and derivation logic
- Null handling, trimming, standardisation and code conversion
- Building requirement traceability and ETL test strategy
03SQL for ETL validation
- SELECT, filters, joins, aggregates and subqueries for reconciliation
- Duplicate and missing record detection
- Date, string, numeric and conditional transformations
- Comparing source and target counts and control totals
- Using CTEs and window functions for complex validation
04Source-to-target and transformation testing
- Schema, metadata, column mapping and datatype validation
- Record-count and aggregate reconciliation
- One-to-one, one-to-many and many-to-one mapping
- Derived columns, calculations, rounding and lookup validation
- Negative, boundary and invalid source data scenarios
05Data quality and warehouse testing
- Completeness, accuracy, consistency, validity and uniqueness
- Fact/dimension relationship and referential integrity
- Surrogate keys, natural keys and unknown/default members
- SCD Type 1 and Type 2 validation
- Late-arriving dimensions and fact records
06Load strategy and incremental testing
- Full refresh versus incremental load validation
- Watermarks, timestamps and CDC behaviour
- Insert, update and delete propagation
- Duplicate prevention and idempotent re-runs
- Backfill, restart, recovery and partial-load handling
07Performance, security and operations
- Volume testing, load windows and query performance basics
- Batch dependencies, scheduling and operational monitoring
- Reject/error tables, quarantine and reconciliation reports
- Data masking, access control and sensitive-data handling
- Audit columns, lineage and evidence retention
08ETL test project and reporting
- Analyse a sample mapping document and derive test scenarios
- Prepare SQL scripts for source-to-target validation
- Execute full and incremental load tests
- Record defects, impact and reconciliation evidence
- Prepare ETL test summary and release recommendation
How you will practise
Learn through instructor-led sessions using realistic, live applications. Then apply each concept through guided assignments on a separate hands-on practice application, with feedback to help you build practical skills and confidence.
Practical exercises and labs
- Validate customer and order source-to-target mappings.
- Test SCD Type 1/Type 2 changes and surrogate-key generation.
- Reconcile counts and totals for full and incremental loads.
- Inject null, duplicate and invalid records and verify reject handling.
Capstone project
Validate a sample sales data warehouse pipeline from source files/relational tables to staging and dimensional targets, including mapping tests, SQL reconciliation, incremental-load checks and defect reporting.
Tools and technologies
SQL client and a sample relational database; ETL platform is selected for the batch (e.g., SSIS, Informatica, Talend or cloud-native service) and must be named before publishing.
Assessment approach
- Module-wise knowledge checks or short practical tasks.
- Hands-on exercise review using an agreed checklist or rubric.
- Final project demonstration and explanation of design decisions, test evidence or outputs, as applicable.
- Completion criteria, attendance requirements and any certificate conditions must be separately approved and published by TrainingRite.
Schedule and fees
Upcoming batch schedules are shared by our TrainingRite team. Please submit an enquiry and our team will contact you by email or phone with the latest schedule. TrainingRite does not publish course fees or discounts on the website. Our counselling team will share the applicable course fee and other details with you by email or phone after you submit an enquiry.
Frequently asked questions
Who should join this course?
QA testers, data testers, BI analysts and professionals validating data warehouse or migration pipelines.
Do I need prior experience?
Basic SQL is recommended. Database fundamentals can be taught as a prerequisite module.
Is the training online?
TrainingRite programmes are delivered online.
Will I get hands-on practice?
Sessions are instructor-led and use realistic applications. You then apply each concept through guided assignments on a separate practice application.
How can I enquire about fees and the next batch?
Fees and batch schedules are not published on the website. Submit the enquiry form on this page and our counselling team will share them with you by email or phone.