Snowflake Interview Questions and Answers

Last updated on Jan 04, 2023
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Snowflake Interview Questions

Snowflake is becoming the most popular cloud data warehouse solution because of its innovative features such as separation of computing and storage, data sharing, and data cleaning. It provides support for popular programming languages like Python, Java, Go, .Net, etc. Tech giants like Adobe systems, AWS, Informatica, Logitech, Looker are using the Snowflake platform to -intensive applications. Thus, there is always a demand for Snowflake professionals. If that is the career move you are making, and you are training or preparing for a Snowflake job interview, the below Snowflake interview questions and answers will help you prepare.

Most Frequently Asked Snowflake Interview Questions

Here in this article, we will be listing frequently asked Snowflake Interview Questions and Answers with the belief that they will be helpful for you to gain higher marks. Also, to let you know that this article has been written under the guidance of industry professionals and covered all the current competencies.

Q1. What means the Snowflake cloud data warehouse?

It is an analytic data warehouse implemented as a SaaS service. Snowflake has been built on a new SQL database engine with an amazing architecture built for the cloud. This cloud-based data warehouse solution was first known on AWS as software to load and analyze massive volumes of data. However, the most unique feature of Snowflake is its capability to spin up any number of virtual warehouses, which indicates that the user can operate an infinite number of independent workloads as opposed to the same data without any risk of contention.

Q2. Explain the Snowflake ETL?

ETL stands for extract, Transform, and Load. ETL is the method that we use for extracting the data from multiple sources and loading it to a particular database or data warehouse. These sources include third-party apps, databases, flat files, etc. Snowflake ETL is a process to apply the ETL approach for loading the data into the Snowflake data warehouse or database. Snowflake ETL also contains extracting the data from the data sources, doing the necessary transformations, and loading the data into Snowflake.

Q3. How many types of databases are in Snowflake?

Snowflake is built-up entirely on a SQL database. Snowflake is a columnar-stored relational database that works well with Excel, Tableau, and many other tools. Snowflake has its query tool, supports multi-statement transactions, role-based security, etc., which are desired in a SQL database.

Q4. Define the Snowflake Cluster

The Snowflake data partitioning is called clustering, and the table is arranged according to cluster keys. Re-clustering refers to the process of managing clustered data in a table.

Q5. What are the features of Snowflake?

Unique features of the Snowflake data warehouse are detailed below:

  • Database and Object Closing
  • Support for XML
  • External tables
  • Hive meta store integration
  • Supports geospatial data
  • Security and data protection
  • Data sharing
  • Search optimization service
  • Result Caching

To gain complete knowledge about snowflake features Snowflake Training helps to a great extent .

Q6. Define Snowflake computing ?

Snowflake cloud data warehouse platform gives instant, secure, and governed access to the entire data network and a core architecture to enable different types of data workloads, including a single platform for developing modern data applications.

Q7. What kind of SQL does Snowflake use?

Snowflake helps the most common standardized version of SQL, i.e., ANSI, for effective relational database querying.

Q8. Which are the cloud platforms currently supported by Snowflake?
  • Microsoft Azure (Azure)
  • Amazon Web Services (AWS)
  • Google Cloud Platform (GCP)
Q9. Explain the ETL tools do you use with Snowflake?

the best ETL tools for Snowflake are as follow:

  • Hevo Data
  • StreamSets
  • Etleap
  • Apache Airflow
Q10. Explain zero-copy cloning in Snowflake?

Snowflake's zero-copy cloning allows us to generate a copy of our tables, databases, and schemas without replicating the data itself. To assume zero-copy in Snowflake, we include using the keyword known as CLONE. Using this action, we can obtain live data from the production and carry out multiple actions.

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