Challenges/calculate-customer-loyalty-tiers-from-transaction-history
DataWeaveADVANCED

Calculate Customer Loyalty Tiers from Transaction History

This challenge involves processing a flat list of customer transactions to calculate total spending per customer and assign them to a loyalty tier. You will practice a powerful combination of aggregation and transformation functions to restructure data from a flat array into an aggregated JSON array. This pattern is essential for building summary reports, analytics payloads, and preparing data for CRM systems.

#rest-api#dwl::core#pluck
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%dw 2.0
output application/json
---
payload
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The fastest way
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01.
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Real CSV/JSON/XML you'll meet on day one — null fields, mixed casing, partial records.
02.
Design problems
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03.
Edge cases that break
Empty arrays, type coercion, deeply nested transforms, locale-specific dates.
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// WHAT YOU'LL BUILDHOW IT WORKS ↓
01.
Live DataWeave editor
Real DWL 2.0 IDE with helpers, modules, syntax highlighting.
02.
Test cases run on real runner
Same Go runner used in prod. Diffs show exactly which fields fail.
03.
3 graded attempts
Submit when you're ready. Score persists. Solution unlocks after pass or last attempt.
04.
Helpers & multi-module DWL
Bring in reusable %dw modules. Import, export, compose.
05.
XP & leaderboard
Points + XP awarded per challenge. Trail progress synced.
06.
Production-style payloads
Real CSV/JSON/XML — null fields, mixed casing, partial records.