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Prepare and test your skills
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A data analyst needs to prepare a summary report in BigQuery that combines customer information with sales transactions. The database contains two tables:
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StudyCertscustomers (columns: customer_id, customer_name)orders (columns: order_id, customer_id, order_amount)The analyst must produce a structured dataset showing each customer's name, the total number of orders placed, and their total spending across all transactions.
Which SQL query should the analyst execute in BigQuery to generate this report?
This query combines tabular data from two distinct tables using a JOIN clause and applies aggregate functions (COUNT and SUM) grouped by a categorical attribute (customer_name) using a GROUP BY clause.
JOIN with the predicate ON c.customer_id = o.customer_id correctly merges the customers table with the orders table using their common key (customer_id).COUNT(o.order_id) aggregate function tallies the total number of order records associated with each individual customer.SUM(o.order_amount) aggregate function calculates the mathematical total of numeric order values for each customer.GROUP BY c.customer_name clause establishes the grouping boundary, ensuring that aggregation functions reduce multiple transaction rows down to a single summary row per customer.customer_name) as a dimension and numeric quantities (order_id counts, order_amount sums) as metrics.Executing transformations and aggregations directly in the underlying database ensures that downstream reports receive precise, pre-summarized data, minimizing processing overhead and avoiding query errors.
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