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Learn Challenge: Analyzing Top Products | Query Engine Basics
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bookChallenge: Analyzing Top Products

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Modern Practice

In the video and course examples, you will see the JSON_EXTRACT function. While this function is fully supported and works correctly, it is considered legacy syntax in BigQuery.

For your own future projects, we recommend using the modern standard functions:

  • JSON_VALUE: extracts scalar values (like strings or numbers) and removes extra quotes automatically;
  • JSON_QUERY: extracts complex JSON objects or arrays.

Write a query that shows sales analysis for our top products using the data in our retail_data_updated table:

  1. Extract product names from the JSON in the 'products' column;
  2. Count how many times each product appears in transactions;
  3. Calculate the total revenue generated by each product;
  4. Group results by product name;
  5. Sort by the most frequently purchased products.

Your query should return these columns:

  • 'product_name' (extracted from JSON);
  • 'purchase_count' (how many times this product appears);
  • 'total_revenue' (sum of transaction amounts where this product appears).
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SectionΒ 2. ChapterΒ 2

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SectionΒ 2. ChapterΒ 2
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