Are you preparing for Snowflake Interviews? Or just curious to know how many Snowflake Interview questions you can answer? No problem. We are here to address your need to crack the SnowFlake interview in the very first attempt.

We have made a list of the most frequently asked Snowflake interview questions and shared it with our subject matter experts for the answers. We have curated the best answers one can use while attending interviews in real-time, which will impress the interviewer of any organization.

For a better understanding of the subject, we recommend you answer the questions with your existing knowledge and then cross-check with our answers. Now let’s dive into the questions.

The questions are divided into different sections based on the experience of an individual. Each section has questions along with curated answers. You may modify the answer with your own language with the same meaning. So, the interviewer won’t feel that you are reading something.

This article covers different Snowflake interview questions and answers in 2023 ranging from basic to advanced. Snowflake is a cloud-based data warehouse platform that interrupted the data warehouse sector with its advanced features and cost-efficiency.

Types of Snowflake Interview Questions

Snowflake Interview Questions and Answers For Freshers

1. Define Snowflake?

Snowflake is a cloud-oriented data warehouse supplied as a Saas (Software-as-a-service) with complete support for ANSI SQL. It has a distinctive architecture that allows users to create tables and begin querying the data with fewer DBA activities required.

2. What are the unique features of Snowflake?

Snowflake is a cloud-based data warehouse. So, it takes the benefits of the capabilities of the cloud and creates the following unique features:

• Autoscaling
• Dedicated virtual warehouses
• Zero copy cloning
• Time travel
• Robust data protection features
• Military-grade security and encryption.

3. Describe Snowflake Architecture?

Snowflake is developed on the shared, multi-cluster, patented data architecture generated for the cloud. Snowflake architecture contains services, storage, and compute layers that are logically integrated but scale indefinitely and separate from one another.

Snowflake Architecture

• Data Storage: In Snowflake, we reorganize the stored data into its intrinsic columnar and optimized format.
• Cloud Services: Cloud services synchronize and manage all the activities throughout the snowflake. It offers the best results for Metadata management, Authentication, and Infrastructure management.
• Query Processing: Virtual warehouses execute the queries in the Snowflake.

4. Explain briefly about Snowflake editions?

Following are the Snowflake editions:

1. Standard Edition: Standard Edition is an initial-level subscription that offers unlimited access to the Snowflake standard features.
2. Business-critical Edition: It provides a higher level of data protection for the critical data of the organization.
3. Enterprise Edition: Besides standard edition services and features, this edition provides extra features necessary for big-scale enterprises.
4. Virtual Private Snowflake: It offers a higher security level for enterprises that are handling financial activities.

5. What are the different methods to access the Snowflake Cloud Datawarehouse?

Methods to access Snowflake cloud data warehouse:

• ODBC Drivers
• Web User Interface
• Python Libraries
• JDBC Drivers

6. What kind of tool is Snowflake?

Snowflake is mentioned as the ETL tool that contains three steps. Therefore, it is a three-stage process. It includes the following three stages:

• Extract: It is the first stage that includes data extraction from the source and creates data files. The data files that we create in this stage support data formats like CSV, JSON, XML, etc.
• Transfer: In this stage, we copy the data into the Snowflake database table through the “COPY INTO” command.
• Load: In this stage, we load the data to internal or external storage. We perform the data staging in the Microsoft Azure Blob and Snowflake-managed locations.

7. What are the benefits of Snowflake Compression?

 The following are the benefits of Snowflake Compression:

• The storage costs of Snowflake compression are less than the native cloud storage because of compression.
• No storage expenses for the disk caches.
• Approximately zero storage expenses for data sharing or data cloning.

[ Check out Snowflake Migration Best Practices ]

8. Describe the Columnar database?

Columnar database arranges the data at column level in place of normal row level. All column levels will be more quickly and utilize fewer resources when compared with the row-level relational database.

9. Explain the data security features of Snowflake?

Snowflake enciphers all the customer data by using end-to-end encryption. The following are the data security features:

• Snowflake automatically encrypts the data through Snowflake-managed keys.
• Through TLS, Snowflake protects all the data transfer and communication between the server and the clients.
• We can select the geographical location where we store the data according to our cloud region.

10. How do we store the data in the Snowflake?

In Snowflake, we store the data in multiple micro partitions, which must be internally optimized and compressed. We store the data in a columnar format in the Snowflake cloud storage. We can access the data objects by executing SQL query operations in Snowflake.

11. What is the role of the storage layer in Snowflake?

The  Storage layer stores all the tables, query results, and data in Snowflake. The storage tier is constructed on extensible cloud spot storage. The design of the storage tier is entirely independent of resiliency, computing resources, and performance for data analytics and storage.

12. Define Snowflake caching?

 Snowflake caches the results of the executed queries. Every time we run a new query, we check the previously executed query. If a matching query is available, we cache the results. After that, we use the cached result set rather than running the query again. So, Snowflake is called global snowflake capture because any number of users can use it.

13. Describe Snowflake computing?

Snowflake cloud data warehouse offers a core architecture that offers instant, managed, and secure access to the complete data network and different kinds of data workloads, which comprises a single platform to develop the latest data applications.

14. Describe zero-copy cloning?

Zero-copy is described as a snowflake clone. We use clones to create a copy of the database schema or table without copying the available storage files on the disk.

Snowflake Interview Questions for Experienced

15. How many kinds of warehouses are available for Snowflake?

Snowflake architecture divides the data warehouses into three unique functions: data storage, cloud services, and compute resources. The price of utilizing Snowflake is according to the utilization of every function.

16. Is it possible to store the enciphered data in the Snowflake?

The benefit of the customer management keys is that we have full control over the master keys for our important management services. If we do not release this key, we cannot decipher the data saved in our snowflake account.

17. Can we connect AWS glue to Snowflake?

Yes, we can connect AWS glue to the Snowflake. As AWS glue is a data warehouse utility, we can connect it easily with the snowflake. By connecting AWS glue and Snowflake, we can process the data more flexibly and easily.

18. Explain briefly about Schema?

In Snowflake, we use schema for organizing the data. Display mode is a logical set of database objects like views and tables. The benefit of using snowflake programs is that they offer organized data and utilize disk spaces.

19. Explain Failsafe?

Failsafe offers a seven-day period, and we can recover the history data by using snow flags. The time period starts instantly after the holding period of the time trip finishes. We do not provide Failure security as a way of using historical data after the retention period finishes.

20. Where do we store the metadata in Snowflake?

Snowflake systematically creates metadata for external or internal stage files. We can store it in a virtual column, and we can query the data through the “SELECT” statement.

21. Describe Snowflake ETL?

 ETL refers to Extract, Transform, and Load. ETL is a process we use for extracting the data from multiple sources and loading it to a particular database or data warehouse. The data sources include third-party applications, databases, flat files, etc. Snowflake ETL means enforcing the ETL process for loading the data into the Snowflake data warehouse or database.

22. Differentiate Horizontal scaling and Vertical scaling

Horizontal scaling increases concurrency when we have to support additional users. We can utilize auto-scaling and raise the number of virtual warehouses to support and satisfy user queries immediately.

Vertical Scaling reduces processing When we have large workloads, and if we want to maximize it and make it run rapidly, we can explore selecting a large virtual warehouse size. 

23. Describe Snowflake Cluster?

 In Snowflake, Data partitions are known as clustering. This generally defines the grouping key for the table. The method of handling cluster data that is available in the table is known as reclustering.

24. How many nodes exist in a big Snowflake warehouse?

A big Snowflake warehouse contains eight nodes. When we run a query on the cluster, we execute the query through a similar number of knots like the parallel node.

25. Why is Snowflake more popular?

Snowflake is more popular due to the following reasons:

1. Snowflake provides a broad range of technology areas like data integration, business intelligence, security, and modern analytics.
2. It offers cloud infrastructure and endorses advanced design architectures ideal for dynamic and agile usage trends.
3. Snowflake endorses unique features like scalable compute, data cloning, data sharing, and the partitioning of the compute and storage.
4. Snowflake streamlines data processing.

26. Is Snowflake OLTP or OLAP?

Snowflake is developed for Online Analytical Processing(OLAP) database system. Based on the utilization, we can use it for Online Transaction Processing(OLTP) intents also.

[ Check Out Best Snowflake Training Courses ]

27. What is the purpose of the Storage Layer in Snowflake?

The storage layer saves all the varied data, query results, and tables. The storage layer is developed on the extensible cloud blob storage. The highest elasticity, scalability, and capacity for data analytics and warehouse are ensured as we engineer the storage for scaling fully autonomous computing resources.

28. What is the role of the computing layer in Snowflake?

In Snowflake, virtual warehouses perform data processing activities. While executing a query, virtual warehouses fetch the minimal data needed from the storage layer for satisfying the query requests.

29. How do we run a Snowflake procedure?

Stored procedures enable us to develop modular code, including complex business logic containing various SQL statements with procedural logic. For running the Snowflake procedure, carry out the below steps:

• Implement a SQL statement.
• Fetch the query results.
• Fetch the result set metadata.

Snowflake Advanced Interview Questions and Answers

30. How do we check the Snowflake history?

For retrieving the activity history details for executing in an executing or scheduled state, query the “TASK_HISTORY” table function in the information schema.

31. Describe Snowflake AWS?

Snowflake provides a data cloud- a global network where several organizations gather data with unlimited concurrency, performance, and scale. Snowflake on AWS acts like a SQL, which makes advance data warehousing efficient, flexible, and available to all users.   

32. What does Snowflake endorse ETL tools?

Snowflake endorses the following ETL tools:

•  Informatica
• Talend
• Tableau
• Matillion.

33. Describe Auto-scaling?

Auto-scaling is a modern property of Snowflake that begins and ends clusters according to the need for the warehouse’s workloads.

34. What are the benefits of Materialized views?

Following are the benefits of the Materialized views:

1. Enhances query performance
2. Snowflake automatically handles materialized views.
3. Materialized views include updated data.

35. Describe Materialized View?

In Snowflake, a Materialized view is a pre-calculated data set originating from the query definition. As the data is pre-calculated, it becomes easy to challenge the materialized view than the materialized view from the base table of the view. Materialized views are developed to improve the query performance for general and repeated query patterns.

36. Explain the Clustering key?

In Snowflake, the Clustering key is a subcategory of the columns in the table that assists in co-locating the data inside the table. It is suitable for conditions where tables are comprehensive.

37. What is Snowflake Schema?

Snowflake Schema is a logical portrayal of the tables in the multidimensional database. A fact table depicts it in the middle with the varied connected dimensions. The main objective of the Snowflake schema is data normalization.

38. What are the benefits of the Snowflake Schema?

The following are the benefits of the Snowflake Schema:

• Utilizes less disk space.
• Minimum data redundancy
• Removes data integration challenges
• Lower Maintenance
• Runs complex queries
• Endorses many-to-many relationships

39. Describe Snowpipe?

Snowpipe is a cost-efficient and continuous utility used to load the data into the snowflake. Snowpipe spontaneously loads the data when they exist on the stage. Snowpipe eases the data loading process by loading the data in small batches and sets the data available for analysis.

40. What are the different types of Caches available in Snowflake?

Following are the different types of catches available in Snowflake:

1. Query Results Cache
2. Metadata Cache
3. Virtual Warehouse Local Disk Caching.

Snowflake Developer Interview Questions

41. Explain the “data shares” option in Snowflake briefly?

In Snowflake, the data shares option enables the users to share the data objects in our database account with other snowflake accounts in a secured manner. The database objects shared between the snowflake accounts are only readable, and we cannot make any modifications to them.

42. What are the different Drivers and Connectors that exist in Snowflake?

Following are the Drivers and Connectors that exist in Snowflake:

• Node.js Driver
• .NET Driver
• ODBC Driver
• JDBC Driver
• Snowflake Connector for Kafka
• Snowflake Connector for Python
• Snowflake Connector for Spark.

[ Check out Apache Spark Tutorial Now ]

43. Explain Micro partitions?

Snowflake has a distinct and robust kind of data partitioning known as micro-partitioning. Data stored in every Snowflake table is automatically transformed into micro partitions. Generally, the micro partition is carried out on all the Snowflake tables.

44. Describe the Time Travel tool?

The time travel tool of Snowflake allows us to use historical data at any specific point within a particular period of time. Through this, we can access the data that has been changed or deleted. Through this tool, we can carry out the following tasks:

• Revive the data objects that have been lost unexpectedly.
• For examining data utilization and modifications made to the data in a specific time period.
• Duplicating and Backing up the data from the essential points in the past.

45. What are the different data-sharing types in Snowflake?

The following are three types of data sharing:

1. Sharing the data among the functional units.
2. Sharing the data between the management units.
3. Sharing the data between geologically distributed locations.

46. What are the advantages of Snowpipe?

 The following are the advantages of Snowpipe:

• Real-time understandings
• User-friendliness
• Cost-efficient
• Zero management
• Flexibility.

47. What is the role of SQL in Snowflake?

The full form of SQL is Structured Query Language, and generally, we use it for data communication. In the SQL, general operators merged into DDL(Data Definition Language) and DML(Data Manipulation Language) to run different statements like UPDATE, SELECT, CREATE, INSERT, DROP, etc. Snowflake supports SQL standard edition. In Snowflake, we use SQL for performing general data warehousing operations like insert, alter, create, delete, update, etc.

[ Learn How to Connect Snowflake in SQL Server ]

48. Explain the Data retention period of Snowflake

The data retention period is an important element of Snowflake, and generally, the data retention period for every Snowflake account is 24 hours(1 day). The data retention period is available for all the Snowflake accounts.

49. How do we secure the data in Snowflake?

Data security is the topmost priority for all organizations. Snowflake applies the best security standards to encrypt and secure the data and customer accounts. It provides leading key management features at no extra cost.

Following are the security steps used by Snowflake to secure our data:

• Snowflake utilizes a managed key to encrypt the data stored in it systematically.
• Snowflake utilizes TLS for protecting the communication between the clients and servers.
• It enables us to choose a geological location for storing our data.

50. What are the different types of tables available in Snowflake?

    Following are the different types of tables available in Snowflake:

1. Permanent: It is a typical database table. It utilizes more space, and we can enable fail-safe and Time-travel periods. Permanent tables are useful for the data that requires a higher level of data recovery and data protection.
2. Transient: In Snowflake, we can create transient tables that exist until externally dropped and are accessible to all the users with relevant privileges.  
3. Temporary: We use the temporary table to store transitory and non-permanent data. Temporary tables exist only in the session in which they were developed.
4. External: External tables are read-only, and we cannot perform DML operations on them. We can use external tables for join and query operations. 

Conclusion

Therefore mentioned Snowflake interview questions are some of the questions asked in Snowflake job interviews and preparing these questions will help you ace the job interviews effortlessly.

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