11 Teradata SQL Interview Questions (Updated 2024)

Teradata frequently asks SQL query questions in interviews for Data Science, Analytics, and & Data Engineering jobs. So, to help you practice for the Teradata SQL interview, we've curated 11 Teradata SQL interview questions – can you answer each one?

11 Teradata SQL Interview Questions

SQL Question 1: Identifying Power Users at Teradata

Teradata, a database and analytics service provider, places a great emphasis on customer engagement. For the purpose of this question, a "power user" is considered as a customer who frequently uses Teradata's services to run queries. In particular, power users are defined as customers who have run more than 100 queries in the past month.

Given the tables , with columns and , with columns , write a PostgreSQL query that identifies the power users for the last month.

Sample Input:

Sample Input:

Please note that all dates are in format.

Answer:

Explanation: This query first identifies customers with more than 100 queries in the last month in the subquery and then joins the result with the users table to get the name of these power users. The clause is used here to filter groups after the clause.

To solve a related customer analytics question on DataLemur's free online SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:

SQL Question 2: Calculate Running Total with SQL Window Functions

Given a business that operates a store both online and offline, it maintains a log of sales happening both on their e-commerce site and physical store. Now, they want to find out the running total of online and offline sales in each month.

Please write a SQL query to calculate the running total of online and offline sales for each month. In the event a month doesn't have any sales, the running total should continue from the last month with a sale.

Below is the table structure and some sample data:

Example Input:

Expected Output:

Answer:

This SQL query uses the window function to calculate running totals, partitioning by (either online or offline) and ordering by the month portion of the . This will give us a running total by month for each type of sale. If there aren't any sales in a month, the running total simply carries over from the last month due to the nature of the window function.

To solve a similar window function interview problem which uses RANK() on DataLemur's free interactive SQL code editor, try this Amazon SQL question asked in a BI Engineer interview:

SQL Question 3: How are left and right joins different from each other?

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Both types of joins in SQL help you retrieve data from multiple tables and merge the results into a single table.

To demonstrate the difference between a left join versus a right join, imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.

A retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.

A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.

SQL Question 4: Filtering Customer Purchases Based on Conditions

Suppose you are a data analyst at an online retail company. You need to extract information about customers who have made at least two purchases in the past 6 months and whose total expenditure exceeds $500. Furthermore, these customers should also have made at least one purchase of above$200 in last one month. For these customers, you need to extract their ID, name, total expenditure, and count of purchases. The information is stored in two tables as given.

example input:

example input:

Answer:

The above query first joins the customers and purchases tables on customer_id. It then restricts to rows where the purchase_date is within the last six months and the amount is greater than $500. The subquery checks for at least one purchase within the last month of more than$200. Finally, the results are grouped by customer_id and name, with having clause ensuring at least 2 purchases, and ordered by total expenditure in descending order.

SQL Question 5: What's the difference between and ?

The clause is used to filter the groups created by the clause. It's similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.

For example, say you were analyzing salaries for analytics employees at Teradata:

This query retrieves the total salary for each Analytics department at Teradata and groups the rows by the specific department (i.e. "Marketing Analytics", "Business Analytics", "Sales Analytics" teams).

The clause then filters the groups to include only Teradata departments where the total salary is greater than $1 million

SQL Question 6: Calculate the Clickthrough Conversion Rate

Teradata is an ecommerce platform where users can browse various digital marketing products and possibly add them to their cart for purchase. A "clickthrough" event occurs when a user views a product and a "conversion" event is recorded when they add the product to their cart. Let's say we have tables that track these two types of events, and :

Example Input:

Example Input:

For the specific point of this question, the goal is to calculate the clickthrough-to-conversion rate, defined as the number of unique conversions (products added to cart) divided by number of unique views (users viewed the product) for each product.

Answer

Here is the PostgreSQL query to find the clickthrough-to-conversion rate for each product:

This query first creates two tables: and . The table contains the count of distinct views for each product and the table contains the count of distinct users who add a product to their cart.

The main query then LEFT JOINS these two tables on , and calculates the clickthrough-to-conversion rate by dividing by for each product.

The functions and are used to handle cases when there are no conversions or views for certain products: will default to 0 if there are no conversions, and will prevent division by 0, returning null instead.

To practice another question about calculating rates, solve this TikTok SQL Interview Question on DataLemur's online SQL coding environment:

SQL Question 7: Could you provide a list of the join types in SQL and explain what each one does?

A join in SQL allows you to retrieve data from multiple tables and combine it into a single set of results.

In SQL, there are four different types of JOINs. To demonstrate each kind, imagine you had two database tables, an advertising campaigns table which had information on Google Ads keywords and how much was bid for each keyword, and a sales table, which has data on how many products were sold and which Google Ads keyword drove that sale.

: An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.

: A LEFT JOIN retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.

: A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.

: A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.

SQL Question 8: Average Selling Price Per Product Category

Given the sales data from the 'sales' table, can you provide the average selling price for each product category for the year 2022? Please group it by product category and month of sale.

Example Input:

Example Output:

Answer:

This PostgreSQL query will calculate the average selling price for each product category on a monthly basis for the year 2022. We first extract the month and year from the 'sale_date' column using the EXTRACT function. Sales from 2022 are filtered and grouped by 'month' and 'product_category'. The average selling price is computed using the AVG aggregate function and the results are ordered by 'month' in ascending and 'avg_sale_price' in descending order.

SQL Question 9: Join and Aggregate Customer and Order Data

Suppose you are given two tables, and . The table holds customer data, and the table stores order information. Each order is associated with a specific customer.

Your task is to write a SQL query that combines both tables to provide insights on total orders and cumulated order value by each customer.

Please refer to the below sample data for both tables.

Example Input:

Example Input:

Answer:

This query joins the and tables based on . It then groups the output by individual customers and counts the total number of orders each customer has. It also sums all order values to find the total order value for each customer. Ultimately, it provides a summary that includes the customer's first and last names, total number of orders they made, and their cumulative order value.

Because joins come up so often during SQL interviews, try an interactive SQL join question from Spotify:

SQL Question 10: What's the difference and a ?

For all practical purposes, and do NOT produce the same results.

While both are similar in that they combine two tables, you can think of joins as increasing the width of the resulting table (you'll have more columns in the result set for a left/inner/right join), whereas a union is used to combine rows which increases the height of the result set but keeps the column count the same.

If your familiar with set operations, you can think of a as set addition, whereas a is set multiplication.

SQL Question 11: Calculations on Product Metrics

You are a data analyst at a e-commerce company and you are responsible for providing insights about the various products sold. Each product has a cost and selling price and you are interested in the profit margin of each product. The profit margin is calculated as .

In addition, you also want to calculate the square root of profit margin and the remainder when the selling price is divided by cost (using mod function). All the values should be rounded off upto 2 decimal places.

Provide the following output:

• product_id
• selling price
• cost
• profit margin (rounded to 2 decimal places)
• square root of profit margin (rounded to 2 decimal places)
• remainder when selling price is divided by cost (rounded to 2 decimal places)

Example Input:

Answer:

This query first calculates the profit margin for each product by subtracting the cost from the selling price and dividing the result by the selling price. It also calculates the square root of the profit margin. Additionally, it gets the remainder when selling price is divided by cost using the MOD function of PostgreSQL. The ROUND function ensures that the results are rounded to 2 decimal places.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating sales metrics per product or this CVS Health Pharmacy Analytics (Part 1) Question which is similar for calculating profit margins per product.

How To Prepare for the Teradata SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Teradata SQL interview is to solve as many practice SQL interview questions as you can! In addition to solving the earlier Teradata SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).

Each interview question has hints to guide you, full answers and most importantly, there is an interactive coding environment so you can right in the browser run your SQL query answer and have it executed.

To prep for the Teradata SQL interview you can also be a great idea to solve SQL problems from other tech companies like:

• MongoDB SQL questions

• Cloudera SQL questions

• Elastic SQL questions

• Couchbase SQL questions

But if your SQL coding skills are weak, forget about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.

This tutorial covers SQL concepts such as LEAD/LAG and aggreage functions like MIN()/MAX() – both of which pop up frequently during Teradata interviews.

Teradata Data Science Interview Tips

What Do Teradata Data Science Interviews Cover?

Besides SQL interview questions, the other types of questions covered in the Teradata Data Science Interview are:

• Probability & Stats Questions
• Python or R Coding Questions
• Product-Sense and Business Case Questions
• Machine Learning and Predictive Modeling Questions
• Behavioral Interview Questions

How To Prepare for Teradata Data Science Interviews?

The best way to prepare for Teradata Data Science interviews is by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from companies like Microsoft, Google & Amazon
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