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.

Modern Practice

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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Dive into the fundamentals of the BigQuery platform and transform the way you handle cloud data. Master the skills needed to navigate the console, manage projects, and optimize query costs. Get hands-on experience with BigQuery-specific features like array operations, geographic data, and date functions. Explore advanced optimization techniques and learn the secrets of building machine learning models directly within the warehouse using BigQuery ML.

Gain a solid understanding of the BigQuery environment. distinct from traditional databases. Learn to navigate the console, manage projects and datasets, and analyze costs effectively. Build confidence in setting up your workspace for efficient data analysis.

Explore the essentials of the Query Engine to retrieve data efficiently. Master data selection techniques and learn how to analyze specific product metrics. Discover performance features and query testing methods to ensure your analysis is both fast and accurate.

Take your knowledge to the next level by mastering BigQuery’s unique data types. Learn to handle complex array operations and manipulate date and time functions. Explore geographic features to solve location-based challenges like calculating city distances.

Optimize your workflow by managing large tables and improving query performance. Learn the secrets of effective error handling to troubleshoot issues quickly. Master the skills needed to maintain a high-performance database environment.

Apply your knowledge to real-world scenarios. Discover how to build comprehensive reports and integrate BigQuery with external tools. Transform raw data into actionable business insights through practical application and reporting strategies.

Dive into the fundamentals of BigQuery ML. Discover how to create and execute machine learning models using standard SQL without moving data. Gain hands-on experience with model walkthroughs to predict outcomes directly within the platform.

Challenge: Analyzing Top Products