Top 25 Snowflake Interview Questions and Answers in 2022


Snowflake Interview Questions and Answers

Snowflake is one of the most common SaaS-based data warehouse platforms globally. It is built on top of Amazon Web Services, Google Cloud infrastructures, and Microsoft Azure and serves companies that need flexible and scalable storage and business intelligence solutions.

You may be interviewed on Snowflakes if you apply for a data management, data engineering, or data science job. Therefore, you should know how to tackle such questions if they ever come your way. We will look at some of the most questions about this SaaS platform to help you ace your upcoming interview. Take a look at the following:

1. What Is Snowflake?

Snowflake is a cloud-based data warehouse platform that offers flexible and scalable storage as well as business intelligence solutions to companies. It is built on top of Microsoft Azure, Google cloud infrastructures, and Amazon Web services, making it an excellent option for data management, data engineering, data lakes, data applications development, and the secure sharing and use of both shared and real-time data. It has greatly changed the data warehousing industry thanks to its centralized nature.

2. What Do You Understand By Snowflake Computing?

Snowflake provides secure, instant, and galvanized access to different data networks by the platform, which further has a core architecture that allows several types of data workloads. Snowflake differs from other data warehouses since it doesn’t utilize big data or a given database. It has a new SQL engine complemented by a unique cloud-based infrastructure, which explains why it is one of the best data platforms.

3. Can You Tell Us About The Three Main Layers Of Snowflake Architecture?

The first is the database storage layer, which reorganizes data into different formats such as optimized, compressed, and columnar once data has been loaded into the platform. This data is then stored in cloud storage. Snowflake also has a query processing layer that executes queries via virtual warehouses. These houses have multiple compute nodes obtained from cloud providers. The last layer is the cloud services layer, which allows the snowflake data cloud administration and management. It offers query parsing, metadata management, authentication, access control, and optimization services.

Why Should We Hire You? 5 Best Answ...
Why Should We Hire You? 5 Best Answers

4. How Do You Normally Access The Snowflake Cloud Data Warehouse?

I have five ways of accessing the stored data in Snowflake. I mostly use ODBC drivers, which easily connect to Snowflake. Other means include JBDC drivers, which empower java applications to interact with different databases; Python libraries where I can create Python applications that connect to Snowflake and perform several operations; web user interface, which performs almost all SQL-related tasks and lastly, SnowSQL Command-line client, a python-based command line that allows easy access to Snowflake from different operating systems.

5. Snowflake’s Main Competitor At The Moment Is Redshift. Do You Have Any Experience With The Latter? And If Yes, Can You Differentiate The Two?

I have interacted with both Redshift and Snowflake and can differentiate them. The main difference is that whereas Redshift combines both computer usage and storage, Snowflake doesn’t and therefore has a different pricing structure for both. Snowflake further offers better JSON storage, making storage and querying JSON with its native functions a reality, whereas Redshift splits JSON into strings, which makes querying and storage quite difficult. Lastly, Snowflake allows data vacuuming and compression automation, a privilege that Redshift users do not. Instead, they have to maintain their systems constantly.

6. Do You Know The Different Stages In Snowflake?

In Snowflake, stages are data storage locations. The platform has three different stages: the user, table, and internal named stages. The user stage is granted to every user by default for file storage, while the table stage is assigned to every table by default as it targets the different database tables. The internally named stages are quite flexible. They are created manually, a process that can be used to specify file formats. All these stages play important roles in Snowflake.

7. What Do You Know About Snowpipe?

Snowflake offers Snowpipe, which is a consistent data intake service. Once files have been added to a given stage and their ingestion approved, the Snowpipe will load them within minutes. This feature allows users to load data in small batches and access the same data within minutes instead of manual processes. It combines file checksums and filenames and therefore processes only new data. All in all, the Snowpipe makes data analysis easier and therefore plays a great role in this platform.

8. Can You Tell Us Some Of The Advantages Of Snowpipe Now That You Have Mentioned It?

Snowpipe has several advantages that users experience. It does away with roadblocks, thereby facilitating real-time analytics. It is also cost-effective and easy to use, catering to beginners and small organizations. You don’t need any management procedures to enjoy its flexibility and resilience. These are one of the reasons why Snowflake is common among large companies.

9. How Does Snowflake Secure Data And Information?

This platform takes data security seriously, just any every other organization. It employs the best security standards for data encryption and safeguarding, partly explaining its popularity. It has an array of free-worthy management features. These security measures include automatic data encryption using a managed key, data security between customers and servers through transport layer security, and selection of geographical location for data storage. All the available standards ensure data privacy, which is key to different establishments.

10. This Platform Offers Scaling Solutions. Can You Mention The Two Types?

Snowflake has horizontal and vertical scaling, which serve different purposes. The latter increases the processing power of a given machine to reduce processing time. It optimizes workload and makes it run faster. On the other hand, horizontal scaling increases concurrency. It uses an auto-scaling function that increases virtual warehouses’ numbers, allowing entities to respond to additional queries swiftly. It comes in handy when the number of customers skyrockets.

11. How Is Snowflake An ETL Tool?

A snowflake is an ETL tool that allows the extraction, transformation, and loading of data. This is normally performed in three main steps that every user should know. First, data is extracted from a given source and saved in different data files and formats such as XML, CSV, and JSON. This data is then loaded into stages or storage locations, internal or external. Internal stages are Snowflake-managed locations, while external stages include Google Cloud, Microsoft Azure, and Amazon S3 Bucket. Lastly, the data is copied into a snowflake database via the COPY INTO command. It is also worth noting that different ETL tools are compatible with Snowflake. These include HevonData, Etleap, Apache Airflow, Matillion, and Blendo.

12. Can You Tell Us About Schema In Snowflake?

A schema is a logical group of database objects such as views and tables. Snowflake schemas, therefore, describe data organization in this platform. One fact table is normally linked to several dimension tables in this SaaS, which further links to other tables, creating an interrelated data network. The fact table stores quantitative data used in analysis and is surrounded by different associated dimensions related to other relative tables, thus leading to a snowflake pattern. It is worth noting that Snowflake tires measurements are in a dimension table while attributes are found in the fact table. All in all, users and customers enjoy a data definition language to create and maintain schemas and databases.

13. Differentiate Star And Snowflake Schemas

Star schemas consist of a fact table and multiple relevant dimension tables. It got its name from its structure, which resembles a star. It has denormalized dimensions even though similar values are repeated within the table. On the other hand, the snowflake schema has a fact table at the center linked to several dimension tables. It is a constant web as the present dimension tables are normally linked to other dimension tables. Unlike the former, snowflake schemas have fully normalized data structures.

14. Snowflake Is Built On Top Of Amazon Web Service. However, Can You Explain How The Two Differ?

The main differences between these two platforms are their pricing, deployment options, and user experience. You don’t need any maintenance with Snowflake, given that it is a complete software as a service while AWS calls for manual maintenance. Secondly, strict security checks are enforced through always-on encryption in Snowflake, while the latter relies on a customizable and flexible means. Lastly, Snowflake has independent storage and computation while AWS combines these two services. Based on the last difference, Snowflake is generally pricier than AWS.

15. How Does Snowflake Perform Data Compression?

Snowflake uses modern data compression algorithms to compress and store data. Customers only pay for the size of the compressed data and not the raw one, which makes this platform a good option for such operations. Some advantages of using Snowflake to compress data include: it doesn’t have storage charges for on-disk caches. It is relatively cheaper as customers only pay for the compressed data, and data sharing and cloning attract no storage costs. This is one of the best data management platforms.

16. Snowflake Allows For Sharing Of Data. Can You Tell Us What You Know About This Platform’s Data Sharing Function?

Snowflake grants organizations the liberty to share data between different accounts safely and securely. The object shared are normally readable and cannot be easily changed or modified. It is worth noting that this platform offers three types of data sharing: Sharing between geographically dispersed locations, sharing between functional units, and sharing between management units. All these three are efficient.

17. How Many Snowflake Editions Do We Have?

There are four Snowflake editions with different offerings. They target different needs and should therefore be chosen wisely. The standard is the entry-level version which allows access to different standard features. The enterprise edition offers more features and services and can serve a large-scale organization. The business-critical and virtual private snowflake editions are the most advanced. The former grants users advanced levels of data security to handle highly sensitive data, while the latter serves exclusive organizations that need top-notch security. It is generally used to collect, analyze and share highly confidential data as it grants the highest level of security.

18. What Can You Tell Us About Snowflake Caching?

Snowflake caching is the storage of query results from all the queries that one runs. It saves time since it checks for the existence of a matching query each time a new one is submitted. If one exists, it will offer the cached results instead of running the new one altogether. There are different types of caching in Snowflake, such as query results caching, local disk caching, and remote disk caching. Query results cashing deals with results obtained in the last 24 hours, while remote disk caching stores results needed in the long term. Lastly, local disk caching stores data used for SQL query performance.

19. What Do You Understand By Time Travel In Snowflake?

Time travel is one of the most important features of Snowflake as it allows one to access historical data stored in the data warehouse. It allows easier retrieval of lost data and deleted or altered data access. Some of the tasks that this feature performs include data manipulations and usage analysis, restoration of data-related objects, and the backup or duplication of data at given points. All these should happen within a given period.

20. Does Snowflake Have A Data Retention Period?

Yes. Every Snowflake account comes with a default retention period of a day. However, other advanced editions, such as enterprise editions, have a retention period of up to 90 days, explaining why one should pay more for Snowflake. This feature preserves the state of a given data before it is updated through modification or alteration. This specifies the number of days a given data set will be preserved, thus permitting time travel operations. This is definitely one of the best features of Snowflake.

21. Have You Ever Heard Of Fail-Safe In Snowflake?

I have a good grasp of this platform owing to the years I have used it. The fail-safe feature gives users a default seven days period in which they can choose to retrieve historical data. The fail-safe period begins after the expiration of the time travel and data retention period. This is usually the last data recovery option and generally works under best-effort conditions. It can also be used to retrieve data that has been damaged through extreme operation failures. However, unlike other data recovery methods offered by Snowflake, it is not instant and can take up to several days.

22. Tell Us About The Process Of Data Storage In Snowflake?

Once a user loads data into Snowflake, it undergoes automatic reorganization into micro-partitions, which are columnar, optimized, and compressed formats. The resultant data is then stored in the cloud, a process managed by Snowflake. The platform does file structuring, sizing, compression, and statistics, among other processes. Such data can only be accessed via SQL queries, which are normally cached for easier retrieval. This platform stores data in columns instead of rows for improved analytical querying and database performance. Such a storage method makes business intelligence more accurate and easier.

23. Why Would You Advise A Company To Use Snowflake?

Snowflake has several pros that a company would appreciate, but mainly that it is affordable, user-friendly, and scalable. Users get a high storage capacity which comes in handy when handling large datasets. Snowflake can also be hosted on several popular cloud platforms such as Amazon Web Services and Google cloud. Other pros include greater server capacity, high-quality data security, and special performance tuning. It is also worth mentioning its quality performance and excellent data recovery.

24. What Are Some Of The Disadvantages Of Using This Platform?

Even though Snowflake comes with several advantages, it also has its shortcomings. First, it only serves semi-structured and structured data, locking out unstructured data formats that should also be supported. Migrating data to Snowflake can also be a task since Snowpipe does not cater to different cases adequately. This platform does not offer any data limit, which is highly disadvantageous even though it looks like an advantage. An entity can easily exceed its data limit only to be slapped with a huge bill. It should offer a data limit in its plans.

25. Why Do You Think Most Organizations Are Turning To This Platform?

Several organizations are turning to Snowflake based on its advantages. First, this platform has excellent security features that prevent data breaches, keeping everything confidential. It also contributes to data modernization by allowing entities to better their data usage during analysis and insight findings. The operational performance and cost of this SaaS are also big selling factors. Businesses can access different services as they wish, thanks to cloud computing. All the benefits that this platform comes with outweigh all the costs.

Conclusion

Most companies are quickly turning to Snowflake. It would be good to get conversant with this platform if you are into data management and warehousing. We have covered some of the questions to expect in a Snowflake interview, and therefore, the ball is currently on your court. Make sure that you prepare well for your upcoming interview. We wish you all the best!

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