Aggregate transactions by status and failure reasons (SQL)

Quick Overview

This question evaluates a candidate's proficiency with SQL aggregation, grouping, window functions, string aggregation, and normalization techniques for summarizing transactional records by status and failure reasons.

Aggregate transactions by status and failure reasons (SQL)

Company: Intuit

Role: Software Engineer

Category: Software Engineering Fundamentals

Difficulty: medium

Interview Round: Online Assessment

You are given a table `transactions` with (at least) the following columns: - `transaction_id` (unique identifier) - `status` (e.g., `SUCCESS`, `FAILED`, `PENDING`, etc.) - `amount` (numeric) - `reason` (nullable text; raw failure reason, often messy/inconsistent) Write a SQL query that outputs one row per `status` with exactly these columns: | status | total_transactions | total_amount | failure_reasons | Where: 1. `total_transactions` = count of transactions in that status. 2. `total_amount` = sum of `amount` for that status. 3. `failure_reasons` = a single string that summarizes the most common **normalized** failure reasons for that status (typically only relevant for failure statuses), built by: - Normalizing the raw `reason` values (e.g., trim whitespace, lowercase, map known synonyms/patterns to a canonical reason). - Counting occurrences by `(status, normalized_reason)`. - Ordering reasons by count descending (and breaking ties deterministically). - Concatenating them into one string (e.g., using `LISTAGG`/`STRING_AGG`) so the final output has only one row per status. Assume your SQL dialect supports window functions and an aggregation function for string concatenation (e.g., `LISTAGG` or `STRING_AGG`).

Quick Answer: This question evaluates a candidate's proficiency with SQL aggregation, grouping, window functions, string aggregation, and normalization techniques for summarizing transactional records by status and failure reasons.

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Oct 13, 2025, 12:00 AM
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You are given a table transactions with (at least) the following columns:

  • transaction_id (unique identifier)
  • status (e.g., SUCCESS , FAILED , PENDING , etc.)
  • amount (numeric)
  • reason (nullable text; raw failure reason, often messy/inconsistent)

Write a SQL query that outputs one row per status with exactly these columns:

| status | total_transactions | total_amount | failure_reasons |

Where:

  1. total_transactions = count of transactions in that status.
  2. total_amount = sum of amount for that status.
  3. failure_reasons = a single string that summarizes the most common normalized failure reasons for that status (typically only relevant for failure statuses), built by:
    • Normalizing the raw reason values (e.g., trim whitespace, lowercase, map known synonyms/patterns to a canonical reason).
    • Counting occurrences by (status, normalized_reason) .
    • Ordering reasons by count descending (and breaking ties deterministically).
    • Concatenating them into one string (e.g., using LISTAGG / STRING_AGG ) so the final output has only one row per status.

Assume your SQL dialect supports window functions and an aggregation function for string concatenation (e.g., LISTAGG or STRING_AGG).

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