Module 3 challenge :Analyze Data to Answer Questions (Google Data Analytics Professional Certificate) Answers 2025
Question 1
You use VLOOKUP but it fails due to extra spaces in names.
✅ TRIM
❌ NOSPACE
❌ VALUE
❌ CUT
Explanation:
TRIM() removes all extra spaces from text except for single spaces between words.
Example:
This cleans “Liza␣␣Campbell” → “Liza Campbell”.
Question 2
To count unique “paid” orders instead of total orders.
✅ COUNT DISTINCT
❌ COUNT
❌ RANGE
❌ RETURN
Explanation:
COUNT DISTINCT counts unique values — avoiding duplicates.
Example:
Question 3
=AVERAGE($C$1:$C$100) — what do the dollar signs ($) do?
✅ Average the values regardless of formula copy
✅ Ensure rows and columns do not change
✅ Create an absolute reference
❌ Perform calculation more efficiently
Explanation:
Dollar signs create absolute references, so $C$1:$C$100 remains constant even when copied to other cells.
Question 4
What will this SQL query return?
✅ All records in Books_table and any matching rows from Biography_table
❌ All records in both tables
❌ All records in Biography_table and matching from Books_table
❌ All rows joined together
Explanation:
A LEFT JOIN keeps all rows from the left table (Books_table), plus matching rows from the right table (Biography_table). Unmatched right-side data will show NULLs.
Question 5
VLOOKUP for Lake Urmia’s water type:
✅ =VLOOKUP(“Urmia”, A2:C10, 3, FALSE)
❌ Others
Explanation:=VLOOKUP(lookup_value, table_array, column_index, [range_lookup])
-
Lookup value:
"Urmia" -
Table range:
A2:C10 -
Column 3 = Water type
-
FALSE = exact match
Question 6
HAVING allows you to filter queries using ____ functions.
✅ Aggregate
❌ GROUP BY
❌ ORDER BY
❌ Join
Explanation:
HAVING filters results of aggregate functions like COUNT(), AVG(), SUM().
Example:
Question 7
Convert number of clicks to numeric values:
✅ VALUE
❌ NUM
❌ PROCESS
❌ EXCHANGE
Explanation:
VALUE() converts text that looks like numbers into real numeric values, enabling calculations.
Question 8
Alias the customer table as “cust”:
✅
❌ FROM customer ALIAS cust
❌ FROM customer NEW cust
❌ FROM customer TO cust
Explanation:AS assigns a table alias for shorthand reference in queries.
Question 9
Benefits of subqueries in SQL:
✅ Subqueries make code more readable and maintainable.
✅ Subqueries can make projects easier and more efficient.
❌ Subqueries can be nested in SET command.
❌ Subqueries cannot be used in the same query.
Explanation:
Subqueries simplify complex logic, improve clarity, and allow for filtering or aggregation within another query.
Question 10
What does this SQL code do?
✅ Selects all columns from transactions on Monday and filters only unavailable ones.
❌ Creates a temporary table
❌ Selects all data from table
❌ Filters Fridays
Explanation:
It first filters for Monday transactions, stores them as a temporary alias (account_table), then filters those where availability='NO'.
Question 11
What does this SQL code do?
✅ Finds employees earning more than the average salary in their department.
❌ Calculates average for all employees
❌ Groups employees by department
❌ Joins employees table with itself
Explanation:
The subquery computes the average department salary, and the main query finds employees exceeding that average.
🧾 Summary Table
| Q# | ✅ Correct Answer(s) | Key Concept |
|---|---|---|
| 1 | TRIM | Remove extra spaces |
| 2 | COUNT DISTINCT | Count unique entries |
| 3 | Absolute reference ($) | Fixed cell ranges |
| 4 | LEFT JOIN | Keep all left table rows |
| 5 | =VLOOKUP(“Urmia”, A2:C10, 3, FALSE) | Lookup exact match |
| 6 | Aggregate | HAVING filters group results |
| 7 | VALUE | Convert text → number |
| 8 | FROM customer AS cust | Table alias |
| 9 | 1 & 4 ✅ | Benefits of subqueries |
| 10 | Filter unavailable Monday transactions | Nested subquery |
| 11 | Employees above dept avg salary | Correlated subquery |