11 SMIC SQL Interview Questions (Updated 2024)

At SMIC, SQL crucial for analyzing semiconductor manufacturing data and optimizing operational efficiency through resource allocation queries. Unsurprisingly this is why SMIC asks SQL query questions during interviews for Data Science, Data Engineering and Data Analytics jobs.

So, to help you ace the SMIC SQL interview, we've curated 11 SMIC SQL interview questions – how many can you solve?

11 SMIC SQL Interview Questions

SQL Question 1: Identify Top Spending Customers at SMIC

Semiconductor Manufacturing International Corporation (SMIC) would like to identify their top spending customers, or "whale" customers, in order to focus on maintaining good business relationships with these highly valuable clients. Please write a SQL query to identify the top 3 customers who have placed the highest total orders in terms of value, based on the assumption that the table lists all orders made by all customers, and that the table contains high-level information about all clients.

- Example Input

- Example Input

Example Output:

Answer:

This query retrieves the and from the table and calculates the total order value for each client by summing the from the table. With the clause, it groups these results by and . The clause then sorts these groups in descending order based on the total order value, and the clause selects only the top 3 companies.

To practice a related customer analytics question on DataLemur's free interactive coding environment, try this Microsoft SQL Interview problem:

SQL Question 2: Analysis of Products Sales

SMIC is a SemiConductor Manufacturing International Company that deals with different types of semiconductors. For this SQL question, let's assume SMIC has an table capturing sales data. The dataset includes an , , , , .

The company is interested in finding out the monthly total quantity of each product sold, and want to see how the sales of each product changes month over month. The goal is to identify the top 5 selling products based on the total quantities sold in descending order for each month.

Example Input:

Example Output:

Answer:

The window function in the subquery monthly_sales is used to calculate the total quantity sold of each product each month. In the main query, the ROW_NUMBER() window function is used to rank sales quantity within each month, and the top 5 products are selected. This solution provides the company with a clear understanding of the performance of its products over time. If there exist two products with the same total_quantity_sold in the same month, the ROW_NUMBER() function will arbitrarily assign a row number, and one of them might not appear in the result.

To solve a similar window function question on DataLemur's free online SQL code editor, solve this Google SQL Interview Question:

SQL Question 3: How does differ from just ?

is used to combine the output of multiple statements into one big result!

Suppose you were a Data Analyst at SMIC working on a Sales Analytics project, and had data on sales leads from both the company's Salesforce CRM and it's legacy Hubspot CRM. To write a query to analyze leads created before 2023 started, across both CRMs, you could use in the following way:

filters out duplicates, so each email/job title/company only shows up once (even if it's in both Salesforce and HubSpot CRMs).

On the other hand, the operator does NOT filter out duplicates, so if a lead shows up in both CRMs, it'll be listed twice in the output of .

SQL Question 4: Filtering Customer Records

Suppose you are working in the customer relationship management department of SMIC. Given a customer database, you are tasked with filtering out active customers in the US who have made at least one purchase exceeding $10,000.

The input table:

And the input table:

Your goal is to write an SQL query to filter the necessary customer records.

Answer:

In the above SQL query is used to combine rows from and tables based on the common column between them, which is . The clause is used to filter active US customers who have made a purchase exceeding $10,000. The keyword is used to return unique customer IDs, in case a customer has made more than one qualifying purchase.

The resulting output will be:

SQL Question 5: What's the difference between a unique and non-unique index?

Unique indexes help ensure that there are no duplicate key values in a table, maintaining data integrity. They enforce uniqueness whenever keys are added or changed within the index.

Non-unique indexes on the other hand, are used to improve query performance by maintaining a sorted order of frequently used data values, but they do not enforce constraints on the associated table.

Unique Indexes are blazing fast. Non unique indexes can improve query performance, but they are often slower because of their non-unique nature.

SQL Question 6: Calculating Click-through conversion rate for SMIC

SMIC, a company that sells electronic components, is interested in analyzing its digital ads performance. Specifically, they would like to understand the click-through conversion rates from viewing an ad to adding a product to the cart. The definition for click-through conversion rate in this case would be the number of times a product is added to the cart after an ad click divided by the number of ads clicked.

You have two tables. The first is a table, which has one row for each click on an ad. The second is a table that has one row for each add-to-cart action by a user.

Example Input:

Example Input:

The question is: Write a SQL query that shows the click through conversion rate for each product.

Answer:

This query first joins the and table using user_id, product_id and ensuring that the click action occurred before the add-to-cart action. It then calculates the conversion rate by dividing the count of add-to-cart actions by the count of clicks for each product.

To practice a related SQL interview question on DataLemur's free online SQL code editor, try this SQL interview question asked by Facebook:

SQL Question 7: Would a UNION ALL and a FULL OUTER JOIN produce the same result?

No, in 99% of normal cases a and do NOT produce the same result.

You can think of more as set addition when it combines the results of two tables.

You can think of a more as set multiplication, producing all combos of table 1 with combos of table 2.

SQL Question 8: Find the average selling price of each type of product, per month, sold by SMIC

SMIC is a semiconductor company that provides various types of chips to its customers. You are given a sales table 'sales', with each row representing a transaction made by SMIC. The 'sales' table includes details such as sales_id, chip_type, sale_date, unit_price, and quantity. Here, chip_type is a categorization of the chip (e.g., Signal processing chips, Memory chips, Logic chips, etc.).

You are required to draft an SQL query that will find out the average selling price of each type of chip per month, spanning all transactions recorded in the 'sales' table.

Example Input:

Example Output:

Answer:

This query first extracts the month from the sale_date using the function. It then groups the sales data by this extracted month and chip_type and finds the average unit price for each group using function. The result is sorted in ascending order by month and chip_type.

SQL Question 9: Filtering Customer Records for SMIC

As an analyst for SMIC, write a SQL query to retrieve all customer records that have a customer_name containing the string 'Tech'. For instance, 'Tech Innovators' and 'Apex Tech' are such customer names.

You have a table named with the following schema:

Example Input

You need to return a table with columns and where the customer_name contains the string 'Tech'.

Example Output:

Answer:

This is a PostgreSQL query that selects the and columns from the table where the contains the string 'Tech'. The '%Tech%' is a pattern with two '%' wildcards in it. The wildcard '%' means "zero or more characters", so any string contains 'Tech' would match the condition.'Tech Innovators', 'Apex Tech', and 'TechNode' are all examples of such names.

SQL Question 10: How do relational and non-relational databases differ?

While knowing this answer is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at SMIC should be at least aware of SQL vs. NoSQL databases.

Relational databases and non-relational (NoSQL) databases have some key differences, particularly in terms of how data is stored. Whereas relational databases have tables, made up of rows and columns, NoSQL databases use various data models like:

• Wide-Column Stores – this database uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row within the same table
• Key-Value Stores – instead of rows and columns, you have keys, where each key is associated with only one value in a collection (similar to a Python dictionary data structure!)
• Graph Stores – instead of rows of data, you have nodes, and then can also have edges between entities (much like a Graph Data Structure for those who've taken a Computer Science data structures & algorithms class)

This added flexibility makes NoSQL databases well-suited for handling non-tabular data or data with a constantly changing format. However, this flexibility comes at the cost of ACID compliance, which is a set of properties (atomic, consistent, isolated, and durable) that ensure the reliability and integrity of data in a database. While most relational databases are ACID-compliant, NoSQL databases may not provide the same level of guarantees.

SQL Question 11: Join and Aggregate Customer and Order Data

Suppose we are given two tables, and . The table contains customer data and the table contains order data.

Your task is to write a SQL query that joins these two tables on the field and calculates the total amount spent by each customer.

Here is some sample data:

Example Input:

Example Input:

Answer:

Here's a PostgreSQL query that would solve this problem:

The above query first joins the and tables on the field. It then calculates the total amount () spent by each customer. The clause is used to group the results by and , and the clause is used to sort the results in descending order based on the total amount spent.

Since joins come up frequently during SQL interviews, try this interactive Snapchat SQL Interview question using JOINS:

How To Prepare for the SMIC SQL Interview

The key to acing a SMIC SQL interview is to practice, practice, and then practice some more! Beyond just solving the above SMIC SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon.

Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there is an online SQL coding environment so you can right online code up your SQL query answer and have it graded.

To prep for the SMIC SQL interview it is also wise to solve interview questions from other semiconductor companies like:

• TSMC SQL questions
• GlobalFoundries SQL questions
• Samsung SQL questions
• Intel SQL questions

In case your SQL skills are weak, don't worry about diving straight into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.

This tutorial covers topics including aggregate functions and handling dates – both of these come up often in SQL job interviews at SMIC.

SMIC Data Science Interview Tips

What Do SMIC Data Science Interviews Cover?

Beyond writing SQL queries, the other types of problems tested in the SMIC Data Science Interview are:

• Statistics & Probability Questions
• Coding Questions in Python or R
• Product Data Science Interview Questions
• Machine Learning and Predictive Modeling Questions
• Behavioral & Resume-Based Questions

How To Prepare for SMIC Data Science Interviews?

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

• 201 Interview Questions from companies like Google, Tesla, & Goldman Sachs
• A Crash Course on SQL, Product-Sense & ML
• Great Reviews (900+ reviews, 4.5-star rating)