Originally published on StrataScratch.
Amazon is an e-commerce giant and one of the most valuable brands in the world. Data collection and analysis is the key to Amazon’s business model. The e-commerce giant uses data to personalize user experience, create and design products, and even to improve the efficiency of their business operations.
Considering the importance of data for its business model, Amazon is always looking for promising data scientists to join its ranks.
During the interview process, you’ll most likely have to write an SQL query to solve a business problem. Interviewers look at how you approach the problem to rate your analytical, comprehension skills, as well as your ability to pay attention to details.
In this article, we’ll solve one of the Amazon data science interview questions to show how to approach these questions the right way.
Basic to Intermediate Concepts Tested in Google SQL Interviews
Amazon processes massive amounts of data every day, so interviewers are looking for candidates who can write efficient code. Overall knowledge of SQL is also important.
Besides displaying these skills during the interview, you’ll need them to excel at your day-to-day job. Once you get it, you need to show good results to stand out and advance your data science career.
Writing efficient SQL queries comes down to using the most appropriate tools the language has to offer.
Let’s take a look at some of the most important concepts tested in Amazon data science Interviews:
Self joins
JOINs are an important feature of SQL with wide potential applications. Knowledge of Self Joins will allow you to work with multiple references of a single table, which is necessary to solve the question outlined in later sections of this guide.
Proficiency in Self Joins includes knowing how to use aliases to reference the same table two or even three times. A good candidate also knows how to give aliases depending on the context to improve readability of the code.
JOIN and ON statements go hand-in-hand, so it’s important to know how to write the latter as well. ON statements describe the relationship between two tables, or in the case of SELF JOINs, the relationship between two references of the same table.
You can use ON statements to filter the records to meet certain criteria. Check out “SQL JOIN Interview Questions” for some examples of using JOINs. Knowing how to set up the condition is essential to get the desired results. Setting up conditions often involves checking equality or doing comparison.
INTERVAL
Lots of SQL questions deal with date and time, so you need to be proficient in date formatting and performing arithmetic operations with date values. INTERVAL function allows you to increase a date value by, for example, one year, or ten days.
In SQL, interval values are essential for performing arithmetic operations on date and time values. An ideal candidate should be able to create a basic interval value using the INTERVAL keyword, to specify the value and time unit, such as ‘10 Days’. It also pays off to know that interval values are case insensitive.
In general, candidates should have at least basic knowledge of adding and subtracting date values, and know what happens to date values after these operations.
The article “SQL Scenario Based Interview Questions” describes the INTERVAL function and arithmetic operations on date-time values in general.
SQL Logical Operators
Proficiency in logical operators is necessary to set up complex conditions. They allow you to find answers for SQL questions where you have to find records that satisfy certain criteria. Being proficient in logical operators means being able to chain them to get the desired result.
In the later sections of this guide, we will solve a question that requires you to use AND and BETWEEN logical operators. However, that’s only the tip of the iceberg, because there are many more types of logical operators in SQL.
To maximize your chances of getting a data science job, learn about all different types of logical operators and have an understanding of possibilities for using logical operators in SQL.
Data Types in SQL
Data type is one of the most important concepts in SQL. All candidates who go into the Amazon data science interview should have some idea of possibilities for working with each data type and possible functions to use with each one.
All aspiring data scientists should be able to find out the data type of a value in SQL. In addition to that, they should be able to explain differences between how humans read values, vs how computers read them. For instance, what makes SQL treat some number values as numbers, but others as text, even if they look like a number?
It will be helpful to know the rules for working with each data type. For example, knowing the fact that numerical values can not contain spaces or commas may help you avoid a mistake.
Casting values
Data science Interview questions are meant to be challenging. Often you need to cast one value type into another to work with it.
It’s essential to know the functions used for transforming values, and their syntax. Some functions have shorthand syntax, which can be useful for readability of the code. One of the right solutions to our question uses double colon syntax to perform arithmetic operations on date values.
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