Preparation
Cleaning, reshaping, and validating data so it is ready for analysis or storage.
8 articles
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Bronze, Silver, Gold: The Medallion Architecture Explained
The medallion architecture organizes a data pipeline into three refinement layers — bronze, silver, and gold — so raw data, cleaned data, and business-ready data never get confused with each other.
🍎 Low Hanging Fruit -
Excel to SQL: Low Hanging Fruit for Making the Switch
A practical roadmap for Excel power users ready to adopt SQL. These are the highest-value, lowest-effort topics to learn first.
🍎 Low Hanging Fruit -
Python Virtual Environments
Isolate project dependencies with virtual environments so your projects stay reproducible and your system Python stays clean.
🍎 Low Hanging Fruit -
Working with Parquet and DuckDB
Use columnar storage and an in-process SQL engine to query millions of rows faster than pandas — without a database server.
🌳 High Hanging Fruit -
Data Cleaning and Validation
Practical techniques for finding and fixing dirty data — missing values, duplicates, type mismatches, and outliers — before it breaks your pipeline.
🍎 Low Hanging Fruit -
Python & Pandas for Data Wrangling
Load messy data into a DataFrame and use pandas to clean, reshape, and prepare it for analysis or storage.
🍎 Low Hanging Fruit -
Organizing Data with SQL
Use SQL to filter, sort, join, and aggregate your data. A practical reference covering the queries you will actually use day to day.
🍎 Low Hanging Fruit -
Working with CSV and JSON
The two most common data formats explained — how to read, write, convert, and handle the edge cases that always come up.
🍎 Low Hanging Fruit