Complex Data Integration and Joins Questions
Handling intricate join scenarios: multi-condition joins, conditional joins with complex logic, joining on date ranges or overlapping time periods, complex left joins with multiple filtering conditions, self-joins for hierarchical or relationship data, handling non-standard relationships between tables. Understanding implications of different join types on row counts, NULL values, and duplicate handling. Designing queries that correctly integrate data from multiple sources while maintaining data integrity and avoiding duplicate counting or missing data.
MediumTechnical
0 practiced
A BI metric requires joining multiple event types into a single timeline per user and ensuring events from different tables are merged without duplication. Describe a SQL approach to union event types, assign a global_event_id, and join to users while preserving source type and preventing duplicates caused by overlapping ingestion windows.
MediumTechnical
0 practiced
You are combining transactional data from two systems that track the same events but with different granularity and overlapping timestamps. Describe a general strategy (including SQL patterns) to merge these sources into a single reporting fact table without double counting events. Include de-duplication, source priority, and timestamp reconciliation.
EasyTechnical
0 practiced
You need to join two datasets from different sources with slightly different key definitions: Orders(source_a_order_id INT, customer_email TEXT) and CRM(customer_id INT, email_address TEXT). Describe and write SQL to perform a robust join on email, considering case sensitivity and leading/trailing whitespace, and explain how you would detect and handle mismatches caused by typos or multiple accounts per email.
MediumTechnical
0 practiced
Write an SQL pattern that prevents row multiplication when joining a fact to multiple related dimension tables (e.g., Customers -> Addresses and Customers -> Emails) where each customer may have multiple addresses and emails. The goal is to compute customer-level metrics (total_spend) without duplication due to join expansion.
MediumTechnical
0 practiced
Given two tables Events(user_id INT, start_ts TIMESTAMP, end_ts TIMESTAMP) representing user sessions, write SQL to find overlapping sessions per user (pairs of session_ids that overlap in time). Provide a query that avoids comparing a session to itself and handles nullable end_ts (treat null as ongoing). Explain performance implications.
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