A retail analytics team needs to report the number of unique customers per store for the past year. The sales table contains billions of rows. The exact count is not required; a close approximation is acceptable. Which function should the analyst use in the query?

APPROX_COUNT_DISTINCT(customer_id)

A financial analyst needs to report the distribution of loan amounts for each branch. The loan_amount column has some extreme outliers. The analyst wants to present a robust summary that is not heavily influenced by outliers. Which set of statistics should they compute?

AVG(loan_amount) and STDDEV(loan_amount) per branch

COUNT(loan_amount) and AVG(loan_amount) per branch

PERCENTILE(loan_amount, 0.25), PERCENTILE(loan_amount, 0.5), and PERCENTILE(loan_amount, 0.75) per branch

MIN(loan_amount), MAX(loan_amount), and AVG(loan_amount) per branch

When analyzing a very large fact table, which query is most appropriate for a quick estimate of the number of unique customers?

SELECT COUNT(DISTINCT customer_id) FROM fact_table;

SELECT APPROX_COUNT_DISTINCT(customer_id) FROM fact_table;

SELECT COUNT(customer_id) FROM fact_table;

SELECT SUM(customer_id) FROM fact_table;

DatabricksCertified Data Analyst Associate

Domain 4Objective 5

Perform Aggregate Operations Such as Count, Approximate Count Distinct, Mean, and Summary Statistics. DATA-ANALYST-ASSOCIATE Practice Questions (Page 1)

Part of the Section 4: Executing queries using Databricks SQL and Databricks SQL Warehouses domain, which makes up ~22% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~8–13 in this domain), expect 1–1 from this objective — we provide 16 practice questions to prepare you well beyond it. (estimate)

16questions here

4free pages

6concepts

Questions 1–5

1application · medium
A retail analytics team needs to report the number of unique customers per store for the past year. The sales table contains billions of rows. The exact count is not required; a close approximation is acceptable. Which function should the analyst use in the query?
Select an answer first
2expert · hard
A financial analyst needs to report the distribution of loan amounts for each branch. The loan_amount column has some extreme outliers. The analyst wants to present a robust summary that is not heavily influenced by outliers. Which set of statistics should they compute?
Select an answer first
3foundation · easy
Which clause is used to group rows that share a common value so that aggregate functions can be applied per group?
Select an answer first
4foundation · easy
A table `events` has a column `user_id` with values: 101, 102, 101, NULL, 103, 102. What does `SELECT COUNT(DISTINCT user_id) FROM events;` return?
Select an answer first
5foundation · easy
When analyzing a very large fact table, which query is most appropriate for a quick estimate of the number of unique customers?
Select an answer first

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Perform Aggregate Operations Such as Count, Approximate Count Distinct, Mean, and Summary Statistics. DATA-ANALYST-ASSOCIATE Practice Questions (Page 1)

Questions 1–5

A retail analytics team needs to report the number of unique customers per store for the past year. The sales table contains billions of rows. The exact count is not required; a close approximation is acceptable. Which function should the analyst use in the query?

A financial analyst needs to report the distribution of loan amounts for each branch. The loan_amount column has some extreme outliers. The analyst wants to present a robust summary that is not heavily influenced by outliers. Which set of statistics should they compute?

Which clause is used to group rows that share a common value so that aggregate functions can be applied per group?

A table `events` has a column `user_id` with values: 101, 102, 101, NULL, 103, 102. What does `SELECT COUNT(DISTINCT user_id) FROM events;` return?

When analyzing a very large fact table, which query is most appropriate for a quick estimate of the number of unique customers?

Keep studying — Section 4: Executing queries using Databricks SQL and Databricks SQL Warehouses