# A daily executive dashboard reads a fact table fed by three sources at three different natural caden Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem A daily executive dashboard reads a fact table fed by three sources at three different natural cadences: mobile events from Kafka (continuous), Stripe payments (15-minute REST), and Salesforce CRM (daily). The current canvas forces all three through one mega-DAG running daily, making the Kafka events 16 hours stale. Apply the multi-cadence framing this section just taught and split into three upstream cadence-specific DAGs plus one downstream daily DAG. Add at least 2 distinct orchestration nodes (one for the streaming/micro-batch upstream cadences, one for the daily downstream join) and ensure three distinct freshness tiers are visible across the sources via slaFreshness labels (real-time/< 1min for Kafka, < 15min for Stripe, < 24h for Salesforce). The downstream daily DAG joins the three upstream raw assets at 5am via the lakehouse asset boundary. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/a-daily-executive-dashboard-reads-a-fact-table-fed-by-three-9eb1d6cb) - [System Design Interview Questions](https://datadriven.io/data-engineering-system-design) - [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep) - [Daily Challenge](https://datadriven.io/daily) --- Source: DataDriven (https://datadriven.io). 100% free data engineering interview prep. Live code execution against Postgres 16, Python 3.11, and Spark sandboxes. No paywall, no premium tier, no signup gate.