Data Prep

Data cleaning, staging, and SQL-ready inputs

Use this path when the hard part is turning messy files, semi-structured payloads, or staging tables into something you can query with confidence.

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Best For

Use this topic path when the bottleneck looks like one of these

When imported CSV, JSON, or copied spreadsheet data needs cleanup before analysis

When a temporary staging step is safer than writing one long transformation query

When semi-structured fields need to stay queryable without pretending they are already relational

When you need realistic seed or test datasets before building reports, joins, or QA checks

Reading Order

A practical way to move through this cluster

You do not have to read these in order, but this sequence is the fastest path from performance fundamentals into real query-tuning decisions.

Data Cleaning with SQL: From Messy to Masterpiece

Start with the cleanup patterns that normalize inconsistent text, dates, and null-heavy imported values.

Working with JSON in SQL: NoSQL Powers in a Relational World

Then handle the cases where raw inputs remain semi-structured instead of becoming fully flattened tables.

How to UNPIVOT Data in SQL with UNION ALL

Use this when the source is spreadsheet-shaped and the first real task is reshaping wide columns into row-based analytical data.

Mastering Temporary Tables in SQL

Use temporary staging once the transformation gets complex enough that intermediate steps need names and checkpoints.

Generating Massive Test Data with SQL (No Scripts Required)

Finish with synthetic data generation so you can test cleanup and import workflows at a more realistic scale.

Tool Workflows

Pair this topic with the right tools

These tool hubs support the same theme from a more practical angle. Read the articles here for explanation, then switch to the matching workflow page when you want to format SQL, inspect schema structure, or debug queries directly.

Conversion

Data import and conversion workflows

Useful when JSON, CSV, spreadsheets, or SQL seed files need to move quickly between application payloads and relational tables.

Open workflow hub

Schema

Schema design, modeling, and migration review

Use this cluster when the challenge is understanding table structure, relationships, migration impact, or how to generate realistic data from a schema.

Open workflow hub

Practice Challenges

Use these challenge pages for faster reps on the same concept cluster

Topic hubs are better for structured reading. Challenge pages are better when you want to switch from reading into hands-on practice without leaving the concept area entirely.

Patients With Condition

Easy

Match patients whose condition list contains a Type I diabetes code without being fooled by partial code overlaps.

Open challenge

2026-04-29

8 min read

How to UNPIVOT Data in SQL with UNION ALL

Learn how to UNPIVOT wide tables into row-based data in SQL using a portable UNION ALL pattern that works well for analysis, cleanup, and reporting.

Read article

2026-01-24

6 min read

Mastering Temporary Tables in SQL

Need to store intermediate results without cluttering your database? Learn when and how to use Temporary Tables for complex analysis.

Read article

2026-01-14

7 min read

Generating Massive Test Data with SQL (No Scripts Required)

Need 1,000 rows to test your query performance? Don't write a Python script. Learn how to use Recursive CTEs to generate massive datasets directly in SQLite.

Read article

2025-12-28

7 min read

Data Cleaning with SQL: From Messy to Masterpiece

Real-world data is dirty. Master 4 essential SQL functions to clean strings, handle NULLs, and fix formatting errors.

Read article

2025-12-15

7 min read

Working with JSON in SQL: NoSQL Powers in a Relational World

Stop choosing between SQL and NoSQL. Learn how to store, query, and filter JSON data directly within your shiny relational database.

Read article