# 8 Woodward SQL Interview Questions (Updated 2024)

Updated on

December 7, 2023

SQL is used all the damn time at Woodward for analyzing aviation and industrial system data. Unsurprisingly this is why Woodward LOVES to ask SQL query questions in interviews for Data Analyst, Data Science, and BI jobs. So, if you're stressed about an upcoming SQL Assessment, we've collected 8 Woodward SQL interview questions to practice – can you solve them?

## 8 Woodward SQL Interview Questions

### SQL Question 1: Identify Woodward's Power Users

Given the Woodward company's database, create a SQL query that identifies their "power users". For Woodward, a power user is defined as a customer who has placed at least 10 orders in the last three months. The information should include the user_id, email, and total amount of orders placed in that period.

##### Example Input:
order_iduser_idorder_dateamount
9811232021-06-01200
9821232021-06-10150
9834562021-05-01300
9847892021-07-10200
9859992021-08-01250
9861232021-09-01200
9871232021-09-10300
9884562021-07-01250
9897892021-09-10200
9901232021-09-20200

To solve a similar VIP customer analysis question on DataLemur's free interactive SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:

### SQL Question 2: Average Daily Sales Per Product

Woodward is a retailer selling various industrial products. They track their daily sales in a SQL database. The following dataset gives a snapshot of this data, where each row represents a single sale:

#### Example Input:

sale_idsale_dateproduct_idsale_price
12022-07-01101100.00
22022-07-0110250.00
32022-07-0110375.00
42022-07-02101125.00
52022-07-0210260.00
62022-07-0210370.00
72022-07-03101110.00
82022-07-0310240.00
92022-07-0310380.00

Your task is to write a SQL query that will calculate the average daily sale price for each product.

This query first groups the sales data on product_id. For each product, it calculates the running average of the sale_price up to that date using the window function .

This running average is calculated from all the preceding rows up to the current row for each product, which gives the average daily sale price for each product.

Pro Tip: Window functions are a popular SQL interview topic, so practice every window function problem on DataLemur

### SQL QUESTION 3: How does and differ?

The clause is used to filter rows from the result set of a , , or statement. It allows you to specify a condition that must be met for a row to be included in the result set.

The clause is used to filter groups created by the clause. It is 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.

Say you were working on a social media analytics project for Woodward.

Here is an example of a SQL query that you might write which uses both the WHERE and HAVING clauses:

This query retrieves the total impressions and average conversions for each platform in the table, the date of the campaign is in January 2023. The rows are grouped by platform and the clause filters the groups to include only those with more than 5000 impressions and an average conversion rate above 0.2.

### SQL Question 4: Inventory Management and Sales Analysis

As the database manager at Woodward, a company that specializes in design, manufacturing, and service of energy control and optimization solutions in aerospace and industrial markets, you are asked to model a database.

The database will keep track of the different products Woodward manufactures, the warehouse where the products are stored (each warehouse is located in a different city), and the sales made for each product in each city.

The necessary information for these tables should include but not limited to:

• Product ID
• Product Name

• Warehouse ID
• City

• Sale ID
• Product ID
• Warehouse ID
• Date of sale
• Quantity sold

The question is: For a given time period, generate a sales report showing total quantity sold and total sales for each product by city.

##### Example Input:
product_idproduct_name
1Aerospace Controller
2Industrial Pump
3Turbine
warehouse_idcity
11New York
22Chicago
33Denver
##### Example Input:
sale_idproduct_idwarehouse_iddate_of_salequantity
10111101/15/2022100
10222202/23/2022200
10333303/06/2022300
10412204/18/2022400
10523305/27/2022500

This query will provide you with the total quantity sold and total sales by product and city for a given time period (replace and with the desired dates). It accomplishes this by joining the three tables on their related keys and summing the quantity and counting the sales grouped by product and city. This result set is conveniently ordered by total sales in descending order to highlight the top selling items.

### SQL QUESTION 5: Can you list the various types of joins in SQL, and describe their purposes?

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 6: What is the difference between SQL operators ‘BETWEEN’ and ‘IN’?

is used to select rows that match a range of values, whereas the operator checks for values in a specified list of values.

For example, say you were a Data Analyst at Woodward and had a table of advertising campaign data.

To find campaigns with between $500 and$10k in spend, you could use BETWEEN`:

To find ad campaigns that were run on Facebook and Google's Display Network, you could use :

### SQL Question 7: Average Amount Spent on Each Order

At Woodward, you are given a database that contains information about orders made by customers. Your task is to find out on average, how much each customer spends per order.

Here is the data you are given:

##### Example Input:
order_idcustomer_iddatetotal_price
5001c1232022-08-01150.00
5002c1232022-08-02200.00
5003c1232022-08-03100.00
5004c4562022-08-0175.00
5005c4562022-08-02100.00
5006c7892022-08-01200.00
##### Example Output:
customer_idavg_spent
c123150.00
c45687.50
c789200.00

This SQL query calculates the average amount spent by each customer by grouping the data by the column, and then applying the AVG function to the column.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating top items within categories or this Alibaba Compressed Mean Question which is similar for finding average number of items/orders.

### SQL Question 8: Calculate Average Product Sales Per Month

As an infrastructure solutions company, Woodward would want to monitor the average sales for each of their products on a monthly basis.

Given the data in the and tables, write a SQL query to calculate the average (mean) sales per month of each product.

##### Example Input:
sale_idproduct_idsale_datequantity
1011572022-06-087
1026542022-06-103
1031572022-06-185
1044982022-07-262
1056542022-07-057
##### Example Input:
product_idproduct_name
157Hydraulic Pump
654Valve Actuator
498Gas Turbine

The following query joins and tables. It extracts the month from the , groups by the product name and month, and calculates the average quantity sold.

##### Example Output:
mthproduct_nameavg_quantity
6Hydraulic Pump6.00
6Valve Actuator3.00
7Gas Turbine2.00
7Valve Actuator7.00

### Preparing For The Woodward SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Woodward SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the earlier Woodward SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups.

Each problem on DataLemur has hints to guide you, step-by-step solutions and most importantly, there's an interactive coding environment so you can right in the browser run your query and have it graded.

To prep for the Woodward SQL interview it is also wise to solve SQL questions from other defense & aerospace contractors like:

However, if your SQL query skills are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.

This tutorial covers things like manipulating string/text data and filtering data with WHERE – both of these pop up routinely during Woodward SQL interviews.

### Woodward Data Science Interview Tips

#### What Do Woodward Data Science Interviews Cover?

For the Woodward Data Science Interview, in addition to SQL query questions, the other types of questions to practice:

• Probability & Stats Questions
• Coding Questions in Python or R
• Product Analytics Questions
• ML Modelling Questions
• Behavioral Interview Questions

#### How To Prepare for Woodward Data Science Interviews?

To prepare for Woodward Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from FAANG & startups
• a crash course on SQL, Product-Sense & ML
• over 900+ 5-star reviews on Amazon