BigQuery for analytics in GCP - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select all columns from a BigQuery table named 'sales_data'.

GCP

SELECT [1] FROM `project.dataset.sales_data`;

Drag options to blanks, or click blank then click option'

AEVERYTHING

B*

CCOLUMNS

DALL

Attempts:

3 left

💡 Hint

Common Mistakes

Using keywords like ALL or COLUMNS which are not valid in this context.

Trying to write out all column names manually.

The asterisk (*) selects all columns from the table in BigQuery SQL.

2fill in blank

medium

Complete the code to count the number of rows in the 'users' table.

GCP

SELECT COUNT([1]) FROM `project.dataset.users`;

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Aall

B1

Cuser_id

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using a specific column name which counts only non-null values in that column.

Using '1' or 'all' which are not valid in COUNT function.

Using COUNT(*) counts all rows in the table regardless of column values.

3fill in blank

hard

Fix the error in the query to filter rows where 'age' is greater than 30.

GCP

SELECT * FROM `project.dataset.customers` WHERE age [1] 30;

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A>

B=

C<

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' which filters only age exactly 30.

Using '<' or '<=' which filter smaller ages.

The '>' operator filters rows where age is greater than 30.

4fill in blank

hard

Fill both blanks to group sales by 'region' and calculate total revenue.

GCP

SELECT region, SUM([1]) AS total_revenue FROM `project.dataset.sales` GROUP BY [2];

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Arevenue

Bregion

Csales

Dtotal

Attempts:

3 left

💡 Hint

Common Mistakes

Grouping by the wrong column.

Summing a column that does not represent revenue.

SUM(revenue) calculates total revenue, and GROUP BY region groups data by region.

5fill in blank

hard

Fill all three blanks to select user_id, count orders, and filter users with more than 5 orders.

GCP

SELECT [1], COUNT([2]) AS order_count FROM `project.dataset.orders` GROUP BY [3] HAVING order_count > 5;

Drag options to blanks, or click blank then click option'

Auser_id

B*

Dorder_id

Attempts:

3 left

💡 Hint

Common Mistakes

Counting the wrong column.

Grouping by a column not selected.

Select user_id, count order_id for orders, and group by user_id to filter users with more than 5 orders.