🧪 SQL ETL Test Scripts — Data Warehouse QA

A professional collection of SQL test scripts, ETL validation queries, and data reconciliation frameworks built from 5+ years of hands-on ETL/DWH QA experience across Healthcare, Hospitality, and Banking domains.

These scripts cover real-world scenarios including Source-to-Target mapping validation, data quality checks, duplicate detection, null analysis, row-count reconciliation, and BI dashboard validation.

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📁 Repository Structure

sql-etl-test-scripts/
│
├── 01_source_to_target_validation/
│   ├── column_mapping_check.sql
│   ├── data_type_validation.sql
│   └── transformation_rule_validation.sql
│
├── 02_data_quality_checks/
│   ├── null_check.sql
│   ├── duplicate_detection.sql
│   ├── referential_integrity_check.sql
│   └── date_range_validation.sql
│
├── 03_row_count_reconciliation/
│   ├── source_vs_target_rowcount.sql
│   ├── incremental_load_validation.sql
│   └── full_load_reconciliation.sql
│
├── 04_snowflake_specific/
│   ├── schema_drift_detection.sql
│   ├── stage_to_warehouse_validation.sql
│   └── time_travel_audit.sql
│
├── 05_business_logic_validation/
│   ├── healthcare_claims_validation.sql
│   ├── banking_transaction_checks.sql
│   └── hospitality_revenue_validation.sql
│
├── 06_dashboard_kpi_validation/
│   ├── tableau_kpi_reconciliation.sql
│   └── report_vs_warehouse_check.sql
│
└── README.md

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🛠️ Tech Stack

Tool	Purpose
Snowflake	Primary DWH — stage and target validation
AWS Redshift	Cloud DWH reconciliation
Oracle / MySQL	Source database validation
SQL (Advanced)	Joins, Window Functions, CTEs, Aggregations

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📋 Script Categories

1. Source-to-Target Validation

Validates that data moves correctly from source to target with all transformation rules applied.

2. Data Quality Checks

Null checks, duplicate detection, referential integrity, and format validation across all key columns.

3. Row Count Reconciliation

Ensures record counts match between source and target for both full and incremental loads.

4. Snowflake-Specific Scripts

Schema drift detection, stage validation, and time travel auditing unique to Snowflake.

5. Business Logic Validation

Domain-specific checks for Healthcare (claims), Banking (transactions), and Hospitality (revenue).

6. Dashboard & KPI Validation

Validates that Tableau/BI dashboard numbers match the underlying warehouse data.

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🚀 How to Use

1. Clone the repository

git clone https://github.com/arunkumararavindhakshan05-sudo/sql-etl-test-scripts.git

2. Navigate to the relevant category folder
3. Open the .sql file in your SQL editor (Snowflake, DBeaver, SQL Workbench, etc.)
4. Replace placeholder values (<source_table>, <target_table>, <schema>) with your actual table names
5. Execute and review results

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👤 Author

Arunkumar Aravindhakshan — Senior ETL/DWH QA Engineer | 5+ Years Experience 🔗 LinkedIn | GitHub