Production Transformation

How can we build a full multi-stage pipeline that deduplicates, validates, and aggregates order data?

Advanced⏱ 3 Minutes⭐ 1970 XP

🤔 THE QUESTION

How can we build a full multi-stage pipeline that deduplicates, validates, and aggregates order data?

💡 WHAT IS IT?

Chaining sequential CTEs (deduplication -> validation -> aggregation) structures end-to-end production data pipelines.

🎯 WHAT IS IT USED FOR?

dbt production models, Spark SQL Lakehouse pipelines, enterprise data warehouse transformations.

💻 EXAMPLE

WITH cleaned_orders AS (
    SELECT *
    FROM (
        SELECT
            *,
            ROW_NUMBER() OVER (
                PARTITION BY order_id
                ORDER BY updated_at DESC
            ) AS rn
        FROM source_orders
    ) ranked
    WHERE rn = 1
),
valid_orders AS (
    SELECT *
    FROM cleaned_orders
    WHERE customer_id IS NOT NULL
    AND amount >= 0
)
SELECT
customer_id,
COUNT(*) AS order_count,
SUM(amount) AS total_spend
FROM valid_orders
GROUP BY customer_id;

🎯 Mission Objectives

Practice typing production-grade SQL code for Production Transformation.

✓ Multi-stage production ELT
✓ Deduplication + Validation + Aggregation
✓ Enterprise pipeline architecture
✓ dbt model design

🚀 Start Mission

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