Skip to main content
PYSPARK • LESSON 281

Scenario: Customer 360 Aggregation Pipeline

How can we merge customer profile dimensions, order history aggregates, and support ticket counts into a single unified 360 view?

Production3 Minutes800 XP
🤔 THE QUESTION

How can we merge customer profile dimensions, order history aggregates, and support ticket counts into a single unified 360 view?

💡 WHAT IS IT?

Joining aggregated behavioral fact tables with master dimension records produces a comprehensive analytical profile.

🎯 WHAT IS IT USED FOR?

Enterprise Customer 360 analytics enabling marketing personalization and customer success interventions.

💻 EXAMPLE
df_cust_orders = df_orders.groupBy("customer_id").agg(sum("amount").alias("lifetime_spend"), count("order_id").alias("order_count"), max("order_date").alias("last_order_date"))
df_c360 = df_customers.join(df_cust_orders, "customer_id", "left")

🎯 Mission Objectives

Practice typing production-grade PySpark code for Scenario: Customer 360 Aggregation Pipeline.

  • Customer 360 architecture
  • Multi-fact aggregation merging
  • Unified analytical profile