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SQL Data Debugging Toolkit (Free Starter)

SQL Toolkit Data Quality Analytics License Status

A practical SQL toolkit for detecting hidden data quality issues in analytics datasets.

This repository contains the free starter edition of the SQL Data Debugging Toolkit.

It includes a small set of SQL validation checks, a structured debugging workflow and an example dataset with built-in data issues.

The Problem

Most data issues in analytics systems are not caused by SQL mistakes but by hidden problems in datasets and pipelines.

Common examples:

• broken joins • duplicate records • missing values • unexpected schema changes • metric spikes • late arriving data

When a dashboard suddenly shows incorrect numbers, analysts often start writing random queries to investigate the issue.

This toolkit provides a structured approach to debugging analytics datasets.

What’s included in the free starter version

The starter edition includes:

• 6 SQL data validation checks • Data debugging checklist (PDF) • Example dataset with built-in data quality issues

These checks demonstrate the debugging framework used in the full toolkit.

Explore the starter toolkit here:

➡ Open starter toolkit

Quick start

  1. Load example_dataset.sql into your SQL environment
  2. Run SQL checks from the starter/SQL_checks folder
  3. Use the data_debugging_checklist.pdf to follow the debugging workflow
  4. Investigate issues detected by the queries

Example SQL check

Example query for detecting duplicate primary keys:

SELECT
    primary_key_column,
    COUNT(*) AS duplicate_count
FROM dataset_table
GROUP BY primary_key_column
HAVING COUNT(*) > 1;

Debugging workflow

The toolkit follows a structured debugging workflow used by analytics teams:

  1. Schema validation
  2. Missing data checks
  3. Duplicate detection
  4. Join integrity validation
  5. Distribution & anomaly detection
  6. Data freshness checks
  7. Business logic validation

This process helps analysts isolate the root cause of data issues faster.

Repository structure

sql-data-debugging-toolkit

starter
│
├── SQL_checks
│   ├── 01_schema_missing_columns.sql
│   ├── 03_null_ratio_check.sql
│   ├── 05_duplicate_primary_key.sql
│   ├── 15_orphan_records.sql
│   ├── 20_metric_spike_detection.sql
│   └── 27_negative_values_check.sql
│
├── example_dataset.sql
├── data_debugging_checklist.pdf
└── README.md

Supported databases

The SQL queries follow ANSI SQL principles and should work with most modern warehouses:

• PostgreSQL • Snowflake • BigQuery • Redshift • DuckDB • SQL Server

Full Toolkit

The full SQL Data Debugging Toolkit includes:

• 30 SQL validation checks • additional debugging templates • extended documentation • a complete data debugging workflow

Full version available here:

SQL Data Debugging Toolkit (Full Version)

Author

Created by Mikolaj Burzykowski

I build practical tools for data analysts, including SQL debugging workflows, Excel dashboards and data validation systems.