BEGINNER • SQL Fundamentals
Data Engineering Playbook #10
This lesson focuses on reduce pipeline latency for a user behavior tracking environment. You will use: python -m venv venv | python etl_script.py | CREATE TABLE events (id SERIAL PRIMARY KEY). The content is designed for practical data engineering execution.
Code Example
-- Data pipeline for user behavior tracking
-- Objective: reduce pipeline latency
CREATE TABLE IF NOT EXISTS staging_events (
id BIGINT,
event_type VARCHAR(50),
created_at TIMESTAMP
);
INSERT INTO staging_events
SELECT id, event_type, created_at
FROM raw_events
WHERE created_at >= CURRENT_DATE - INTERVAL '1 day';
-- Verify: python -m venv venvCommands & References
- python -m venv venv
- python etl_script.py
- CREATE TABLE events (id SERIAL PRIMARY KEY)
Lab Steps
- Prepare environment with: python -m venv venv
- Design or modify the data pipeline for the scenario.
- Validate data quality and document lineage.
- Propose one optimization for production.
Exercises
- Add one data quality check.
- Implement one incremental loading pattern.
- Write a rollback procedure for this pipeline.