Browse [LATEST] Snowflake Interview Questions and Answers
Last updated on 22nd Sep 2022, Blog, Interview Question
1. What is Snowflake cloud data warehouse?
Snowflake is an analytic data warehouse implemented as SaaS service. It is built on new SQL database engine with unique architecture built for a cloud. This cloud-based data warehouse solution was first available on the AWS as software to load and analyse massive volumes of data. The most remarkable feature of a Snowflake is its ability to spin up any number of the virtual warehouses, which means the user can operate an unlimited number of an independent workloads against a same data without any risk of contention.
2. Is Snowflake is an ETL tool?
Yes, Snowflake is ETL tool. It’s has three-step process, which includes:
- Extracts data from a source and creates data files. Data files support a multiple data formats like JSON, CSV, XML, and more.
- Loads data to internal or external stage. Data can be staged in the internal, Microsoft Azure blob, Amazon S3 bucket, or Snowflake managed location.
- Data is copied into the Snowflake database table usinga COPY INTO command.
3. Explain a Snowflake ETL?
ETL is the process that use for extracting the data from the multiple sources and loading it to a specific database or data warehouse. The sources are the third party apps, databases, flat files, etc.
Snowflake ETL is an approach to applying an ETL process for loading the data into the Snowflake data warehouse or database. Snowflake ETL also included an extracting the data from the data sources, doing the necessary transformations, and loading the data into a Snowflake.
4. How is data stored in a Snowflake?
Snowflakes stored the data in multiple micro partitions which are internally optimized and also compressed. The data is stored in the columnar format in the cloud storage of a Snowflake. The data objects stored by a Snowflake cannot be accessed or visible to the users. By running SQL query operations on the Snowflake, you can access them.
5. How is Snowflake distinct from a AWS?
Snowflakeprovide a storage and computation independently, and storage cost is similar to the data storage. AWS handles this aspect by inserting a Redshift Spectrum, which enables data querying instantly on S3, yet not as continuous as a Snowflake.
6. What type of database is a Snowflake?
Snowflake is built entirely on the SQL database. It’s a columnar-stored relational database that works well with an Excel, Tableau, and many other tools. Snowflake contains its query tool, supports multi-statement transactions, role-based security, etc., which are expected in SQL database.
7. Can AWS glue connect to a Snowflake?
Definitely. AWS glue presents the comprehensive managed environment that simply connects with Snowflake as a data warehouse service. These two solutions collectively enable to handle data ingestion and transformation with the more ease and flexibility.
8. Explain a Snowflake editions.
Snowflake offers a multiple editions depending on the usage requirements.
Standard edition:Its introductory level offering provides a unlimited access to the Snowflake’s standard features.
Enterprise edition: Along with the Standard edition features and services, offers additional features required for a large-scale enterprises.
Business-critical edition: Also, called an Enterprise for Sensitive Data (ESD). It provide a high-level data protection for sensitive data to organization needs.
9. Define a Snowflake Cluster
In Snowflake, data partitioning is called a clustering, which specifies cluster keys on a table. The method by which manage clustered data in a table is called re-clustering.
10. Explain the Snowflake architecture
Snowflake is built on the AWS cloud data warehouse and is truly Saas offering. There is a no software, hardware, ongoing maintenance, tuning, etc. needed to work with Snowflake.
Three major layers make the Snowflake architecture – database storage, query processing, and cloud services.
Data storage: In Snowflake, the stored data is reorganized into an internal optimized, columnar, and optimized format.
Query processing: Virtual warehouses process a queries in Snowflake.
Cloud services: This layer coordinates and handles all the activities across the Snowflake. It provides a best results for Authentication, Metadata management, Infrastructure management, Access control, and Query parsing.
11. What are the features of a Snowflake?
- Database and Object Closing
- Support a XML
- External tables
- Hive meta store integration
- Supports a geospatial data
- Security and data protection
- Data sharing
- Search optimization service
- Table streams on an external tables and shared tables
- Result Caching
12. Why is a Snowflake highly successful?
- It assists a wide variety of a technology areas like data integration, business intelligence, advanced analytics, security, and governance.
- It offers a cloud infrastructure and supports advanced design architectures ideal for a dynamic and quick usage developments.
- Snowflake supports predetermined features like a data cloning, data sharing, division of computing and storage, and directly scalable computing.
- Snowflake is eases data processing.
- Snowflake offers extendable computing power.
- Snowflake suits different applications like ODS with the staged data, data lakes with data warehouse, raw marts, and data marts with acceptable and the modelled data.
13. Tell me something about Snowflake AWS?
For managing today’s data analytics, companies rely on the data platform that offers rapid deployment, compelling performance, and on-demand scalability. Snowflake on an AWS platform serves as a SQL data warehouse, which made modern data warehousing effective, manageable, and accessible to all the data users. It enables a data-driven enterprise with secure data sharing, elasticity, and per-second pricing.
14. Describe Snowflake computing.
Snowflake cloud data warehouse platform offers an instant, secure, and governed access to a entire data network and a core architecture to enable various types of the data workloads, including a single platform for the developing a modern data applications.
15. What is a schema in Snowflake?
Schemas and databases used for an organizing data stored in a Snowflake. A schema is the logical grouping of database objects such as tables, views, etc. The benefits of using a Snowflake schemas are it provides structured data and uses small disk space.
16. What are the benefits of Snowflake Schema?
- In a denormalized model, used a less disk space.
- It provides the good data quality.
17. Differentiate Star Schema and Snowflake Schema?
Both Snowflake and Star Schemas are the identical, yet the difference exists in a dimensions. In Snowflake, normalise only a few dimensions, and in the star schema, hen denormalise the logical dimensions into a tables.
18. What kind of a SQL does Snowflake use?
Snowflake supports the most general standardized version of the SQL, i.e., ANSI for powerful relational database querying.
19. What are the cloud platforms currently supported by a Snowflake?
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Microsoft Azure (Azure)
20. What ETL tools do use with Snowflake?
- Hevo Data
- Apache Airflow
21. Explain a zero-copy cloning in Snowflake?
In Snowflake, Zero-copy cloning is a implementation that enabled us to generate a copy of the tables, databases, schemas without replicating the actual data. To carry out a zero-copy in Snowflake, have to use the keyword known as CLONE. Through this action, can get the live data from the production and carry out the multiple actions.
22. Explain “Stage” in a Snowflake?
In Snowflake, the Stage acts as a middle area that use for uploading the files. Snowpipe detects a files once they arrive at the staging area and systematically loads them into Snowflake.
- Table Stage
- User Stage
- Internal Named Stage
23. Explain data compression in Snowflake?
All the data enter into the Snowflake gets compacted to systematically. Snowflake utilizes a modern data compression algorithms for compressing and storing a data. Customers have to pay for a packed data, not the exact data.
24. How do secure the data in a Snowflake?
Data security plays the prominent role in all enterprises. Snowflake adapts the best-in-class security standards for an encrypting and securing the customer accounts and data that store ina Snowflake. It provides an industry-leading key management features at no extra cost.
25. Explain Snowflake Time Travel?
Snowflake Time Travel tool allows us to accessa past data at any moment in the specified period. Through this, can see the data that can change or delete. Through this tool, can carry out a following tasks:
- Restore data-associated objects that may have a lost unintentionally.
- For examining data utilization and changes done to a data in a specific time period.
- Duplicating and backing up data from an essential points in history.
26. What is a database storage layer?
Whenever load the data into a Snowflake, it organizes the data into compressed, columnar, and optimized format. Snowflake deals with the storing the data that comprises a data compression, organization, statistics, file size, and other properties associated with data storage. All the data objects store in the Snowflake are inaccessible and also invisible. Can access the data objects by an executing the SQL query operation through Snowflake.
27. Explain Fail-safe in a Snowflake?
Fail-safe is modern feature that exists in a Snowflake to assure data security. Fail-safe plays the vital role in the data protection lifecycle of the Snowflake. Fail-safe offers a seven days of additional storage even after a time travel period is completed.
28. Explain the Virtual warehouse?
In Snowflake, a Virtual warehouse is a one or more clusters endorsing users to carry out the operations like queries, data loading, and other DML operations. Virtual warehouses approved a users with the necessary resources like temporary storage, CPU for performing a various snowflake operations.
29. Explain Data Shares?
Snowflake Data sharing allows an organizations to securely and immediately share their data. Secure data sharing an enabled sharing of the data between the accounts through the Snowflake secure views, database tables.
30. What are thedifferent ways to access the Snowflake Cloud data warehouse?
- ODBC Drivers
- JDBC Drivers
- Web User Interface
- Python Libraries
- SnowSQL Command-line Client
31. Explain a Micro Partitions?
Snowflake comes along with the robust and unique kind of data partitioning known as micro partitioning. Data that exists in a Snowflake ables are systematically converted into a micro partitions. Generally, perform Micro partitioning on Snowflake tables.
32. Explain a Columnar database?
The columnar database is opposite to a conventional databases. It saves the data in columns in the place of rows, eases the method for analytical query processing and offers high incredible performance for databases. Columnar database eases analytics processes, and it is future of a business intelligence.
33. How to create Snowflake task?
To create Snowflake task, to use the “CREATE TASK” command. Procedure to create the snowflake task:
- CREATE TASK in a schema.
- USAGE in a warehouse on task definition.
- Run SQL statement or stored procedure in a task definition.
34. How do create a temporary tables?
To create a temporary tables, to use the following syntax:
- Create a temporary table mytable (id number, creation_date date);
35. Where do store data in a Snowflake?
Snowflake systematically creates a metadata for the files in an external or internal stages. store metadata in a virtual columns, and can query through a standard “SELECT” statement.
36. Does a Snowflake use Indexes?
No, Snowflake does not use an indexes. This is one of the aspects that set a Snowflake scale so good for the queries.
37. How is Snowflake distinct from the AWS?
Snowflake offers a storage and computation independently, and storage cost is similar to the data storage. AWS handles this aspect by an inserting Redshift Spectrum, which enables data querying instantly on a S3, yet not as continuous as a Snowflake.
38. How do execute a Snowflake procedure?
Stored procedures allow us to create a modular code comprising complicated business logic by adding different SQL statements with procedural logic. For executing a Snowflake procedure, carry out the below steps:
- Run a SQL statement.
- Extract a query results.
- Extract a result set metadata.
39. Does Snowflake maintain the stored procedures?
40. Is Snowflake is a OLTP or OLAP?
Snowflake is developed for a Online Analytical Processing(OLAP) database system. Subject to a usage, and can utilize it for OLTP(Online Transaction processing) also.
41. How is Snowflake is distinct from Redshift?
Both Redshift and Snowflake provide a on-demand pricing but vary in the package features. Snowflake splits a compute storage from usage in its pricing pattern, whereas a Redshift integrates both.
42. What is the use of a Cloud Services layer in a Snowflake?
The services layer acts as a brain of the Snowflake. In Snowflake, the Services layer authenticates user sessions, applies security functions, offers management, performs optimization, and an organizes all the transactions.
43. What is a use of the Compute layer in the Snowflake?
In Snowflake, Virtual warehouses performed all the data handling tasks. Which are multiple clusters of a compute resources. While performing a query, virtual warehouses extract least data needed from a storage layer to satisfy the query requests.
44. What is Unique about a Snowflake Cloud Data Warehouse?
Snowflake is a cloud native (built for the cloud).So, It takes an advantage of all the good things about the cloud and brings exciting a new features like:
- Auto scaling.
- Zero copy cloning.
- Dedicated to virtual warehouses.
- Time travel.
- Military grade an encryption and security.
- Robust a data protection features.
Snowflake is a poetry. It’s beautifully crafted with a smart defaults :
- All the data is the compressed by a default.
- All the data is an encrypted.
- Its Columnar, thereby making a column level analytical operations a lot faster.
45. What is a Snowflake Architecture ?
Snowflake is built on the patented, multi-cluster, shared data architecture created for a cloud. Snowflake architecture is comprised of a storage, compute, and services layers that are logically an integrated but scale infinitely and independent from one another.
46. What does the Storage Layer do in a Snowflake ?
The storage layer stores all the diverse data, tables and query results in a Snowflake. The Storage Layer is built on the scalable cloud blob storage Maximum scalability, elasticity, and performance capacity for the data warehousing and analytics are assured since a storage layer is engineered to scale completely independent of a compute resources.
47. What does the Compute Layer do in a Snowflake ?
All data processing tasks within a Snowflake are performed by the virtual warehouses, which are one or more clusters of a compute resources. When performing a query, virtual warehouses retrieved the minimum data required from a storage layer to full fil the query requests.
48. What does the Cloud Services Layer do in a Snowflake ?
The services layer is a brain of Snowflake. The services layer for a Snowflake authenticates user sessions, provides management, enforces security functions, performs query compilation and an optimization, and coordinates all transactions.
49. What is Columnar database and what are its benefits ?
Columnar databases organize a data at Column level instead of the conventional row level. All Column level operations will be much faster and consume a less resources when compared to row level relational database.
50. What is a Snowflake Caching ?
Snowflake caches a results of every query that ran and when a new query is submitted, it checks previously executed queries and if matching query exists and the results are also still cached, it uses the cached result set instead of an executing the query. Snowflake Cache a results are global and can be used across users.
51. What are the various types of caching in Snowflake ?
- Query Results Caching.
- Virtual Warehouse Local Disk Caching.
- Metadata Cache.
52 . What is the use of a Snowflake Connectors?
The Snowflake connector is piece of software that allows us to connect to a Snowflake data warehouse platform and conduct activities like Read/Write, Metadata import, and Bulk data loading.
The Snowflake connector can be used to an execute a following tasks:
- Read data from or publish data to tables in a Snowflake data warehouse.
- Load data in a bulk into a Snowflake data warehouse table.
- You can insert or bulk load data into the numerous tables at the same time by using the Numerous input connections functionality.
- To lookup records from the table in the Snowflake data warehouse.
53 .What are the types of a Snowflake Connectors?
- Snowflake Connector for Kafka.
- Snowflake Connector for Spark.
- Snowflake Connector for Python .
54. What is Fail-safe in Snowflake?
Fail-safe is an advanced feature available in a Snowflake to ensure data protection. This plays an important role in the Snowflake’s data protection lifecycle. Fail-safe offers a 7 days extra storage even after a time travel period is over.
55. Why fail-safe instead of a Backup?
- To minimize risk factor, DBA’s traditionally execute a full and incremental data backups at regular intervals.
- This process occupies more storage space, sometimes it may be a double or triple. Moreover, the data recovery process is so costly, takes time, requires business downtime, and more.
- Snowflake comes with the multi-datacenter, redundant architecture that has a capability to minimize the need for traditional data backup. Fail-safe features in the Snowflake is an efficient and cost-effective way that substitutes the traditional data backup and an eliminates the risks and scales along with the data.
56.What is a Data retention period in Snowflake?
Data retention is one of a key components of Snowflake and the default data retention period for all the snowflake accounts is 1 day (24 hours). This is default feature and applicable for all the Snowflake accounts.
57. Explain a data shares in Snowflake?
The data shares option in a snowflake allows the users to share the data objects in a database in the account with other snowflake accounts in a secured way. All database objects shared between the snowflake accounts are only readable and one can not make any changes to them.
- Secure views
- External tables
- Secure UDFs
- Secure materialized views
58. What are the data sharing types in a Snowflake?
- Sharing a Data between functional units.
- Sharing a data between management units.
- Sharing a data between geographically dispersed location.
59 .What do know about a zero-copy cloning in Snowflake?
Zero copy cloning is a snowflake implementation that allows to create a copy of a schemas, tables, databases without copying the actual data. In order to perform zero-copy in the Snowflake, need to use a keyword called CLONE. With this option, can get a real-time data from production and perform a multiple actions.
60. Name the cloud platforms supported by a Snowflake?
- Google Cloud Platform (GCP).
- Amazon Web Services (AWS).
- Microsoft Azure (Azure).
61. What are different Snowflake editions?
- Standard Edition.
- Enterprise Edition.
- Business Critical Edition.
- Virtual Private Snowflake (VPS) Edition.
62.What are the Drivers available in a Snowflake?
- Go Snowflake Driver
- Node.js Driver
- JDBC Driver
- .NET Driver
- ODBC Driver
- PHP PDO Driver for Snowflake
63 .What is a “Stage” in Snowflake?
A stage in Snowflake is explained as an intermediate area used to upload files. Snowpipe Identifies the files as soon as they can enter the staging area and automatically loads them into snowflake.
Following are the three various stages supported by Snowflake:
- User Stage
- Table Stage
- Internal Named Stage
64. What is a Snowpipe in Snowflake?
Snowpipe is continuous, and cost-effective service used to load data into a Snowflake. The Snowpipe automatically loads a data from files once they are available on stage. This process simplifies the data loading process by loading a data in micro-batches and makes data ready for analysis.
65. What are the benefits of a using Snowpipe?
- Real-time insights
- Ease of use
- Zero Management
66. What is virtual warehouse in Snowflake?
A Virtual warehouse in Snowflake is explained as one or more compute clusters supporting users to perform operations like data loading, queries, and many other DML operations. Virtual warehouses support a users with the required resources like CPU, temporary storage, memory, etc, to perform different Snowflake operations.
67. What are the Snowflake views?
Views are useful for displaying a certain rows and columns in one or more tables. A view made it possible to obtain a result of a query as if it were a table. The CREATE VIEW statement explains the query. Snowflake supports a 2 different types of views:
1.Non-materialized views (often referred to as “views”): The results of a non-materialized view are obtained by an executing the query at the moment the view is referenced in the query. When compared to the materialised views, performance is slower.
2.Materialized views: Although named as a type of view, a materialised view behaves more like a table in many aspects. The results of a materialised view are stored in a similar way to that of a table. This allows for the faster access, but it necessitates storage space and active maintenance, both of which an incur extra expenses.
68. What are the programming languages supported by a Snowflake?
Snowflake supports a different programming languages such as Go, Java, .NET, Python, C, Node.js, etc.
69 .What are micro partitions in a Snowflake?
Snowflake comes with unique and powerful form of data partitioning called a micro-partitioning. Data resided in all snowflake tables is automatically converted into a micro partitions. In general Micro partitioning is performed on all the Snowflake tables.
70. What is Clustering in a Snowflake?
Clustering in Snowflake is explained as grouping a bunch of values into a record or file to enhance a query performance.
71.What is Clustering key?
The clustering key in Snowflake is subset of columns in a table that helps us to co-locating data within the table. It is best suitable for a situations where tables are extensive; the order was not perfect due to the DML.
72.What is an Amazon S3?
Amazon S3 is a storage service that provide a high data availability and security. It provides streamlined process for an organizations of all sizes and industries to store their data.
73. What is Snowflake Schema?
The Snowflake schema is explained as a logical representation of tables in the multidimensional database. A fact table represents it in a middle with a diversified connected dimensions. Snowflake schema’s primary goal is to a normalize data.
74.Name a few advantages that arise out of a data compression in a Snowflake?
- Lowers a storage costs.
- Less a disk space.
- Near zero storage overhead for the data sharing or data cloning.
- Byte order-independent.
75. What makes a Snowflake so fast?
Unlike previous technologies where save data in a rows and columns, Snowflake stores data in a blocks by compressing the data. This allows query processing to be much faster compared to a fetching rows.
76. What are the advantages of a Snowflake Schema?
- Uses a less disk space.
- Minimal data redundancy.
- Eliminates a data integration challenges.
- Less maintenance.
- Executes difficult queries.
- Supports to many-to-many relationships.
77.What is a Materialized view in Snowflake?
A materialized view in a Snowflake is a pre-computed data set derived from query specification. As the data is pre-computed, it becomes far simpler to query materialized view than a non-materialized view from a view’s base table.
78 .What are the advantages of a Materialized Views?
- Improves a query performance.
- Snowflake automatically manages the materialized Views.
- Materialized views offer updated data.
79. What is the use of a SQL in Snowflake?
SQL stands for Structured Query Language and is the general language used for data communication. Within SQL, common operators are clubbed into DML (Data Manipulation Language) & DDL (Data Definition Language) to perform a different statements such as SELECT, UPDATE, INSERT, CREATE, ALTER, DROP, etc.
Snowflake is data warehouse platform and supports a standard version of SQL. Using SQL in Snowflake, and can perform the typical data warehousing operations like create, insert, alter, update, delete, etc.
80.What are the ETL tools supported by a Snowflake?
- Talend, etc.
81. Where the metadata gets stored in a Snowflake?
In snowflake, the Metadata is stored in a virtual columns that can be queried using the SELECT statement and loaded into table using the COPY INT command.
82. What is an Auto-scaling in Snowflake?
Autoscaling is an advanced feature in the Snowflake that starts and stops clusters based on a requirement to support workloads on the warehouse.
83. What is the use of Stored Procedures in a Snowflake?
84. Which command is used to create stored procedure?
In Snowflake “CREATE PROCEDURE” command is used to create the stored procedure.
85. What are the advantages of stored procedures in a Snowflake?
- Supports to procedural logic.
- Allows dynamic creation and execution of a SQL statements.
- Helps in an error handling.
- Allows Stored procedure owner to delegate a power to users.
- Eliminates the need for a multiple SQL statements to perform a task.
86.Snowflake Stored procedures are written in?
87. What is a Secure data sharing in a Snowflake?
Secure data sharing helps users to share a selected objects in the database with the other snowflake accounts.
88. Name a few Snowflake database objects that can be shared by using a Secure data sharing?
- Secure views.
- External tables.
- Secure UDFs.
- Secure materialized views.
89. What are the internal and external stages in a Snowflake?
Internal Stage: Here the files are stored within a Snowflake account.
External Stage: Here the files are stored in external location. For instance AWS S3.
90. What is “Continuous Data Protection” (CDP) in a Snowflake?
Continuous Data Protection (CDP) is essential feature offered by a Snowflake to protect data stored in snowflake from events like malicious attacks, human error, and software or hardware failovers. This CDP feature makes data accessible and recoverable at all stages of the data life cycle even if lost it accidentally.
91 .What is a Snowflake?
Snowflake is a cloud data warehouse offer as a software-as-a-service (SaaS). It consists of an unique architecture to handle multiple aspects of data and analytics. Snowflake sets itself apart from all the other traditional data warehouse solutions with advanced capabilities like an improved performance, simplicity, high concurrency and cost-effectiveness.
Snowflake’s shared a data architecture physically separates a computation and storage which is not possible by the traditional offerings. It streamlines the process for the businesses to store and analyze massive volumes of data using a cloud-based tools. Snowflake has transformed the data warehouse industry by making it possible to bring all the data together into a centralized system.
92.What is unique about a Snowflake Architecture?
This architecture simplifies a data management with a shared-disk architecture and adds performance and scalability advantages with shared-nothing architecture. Snowflake unique architecture consists of a three layers which are database storage, Query processing, and Cloud services.
93. What skills are needed for a Snowflake?
- Competent a programming knowledge.
- Data Analysis and a Visualisation skills .
- In-depth understanding of a data warehouse and ETL concepts.
- Familiarity with the SQL.
- Proficiency with the SnowSQL .
94. What is the Query Processing layer in a Snowflake architecture?
All the query executions are performed in this processing layer.. Each virtual warehouse is an MPP (massively parallel processing) compute a cluster which consists of multiple nodes allotted by a snowflake from a cloud provider.
Every virtual warehouse in the query processing layer is an independent and does not share its computational resources with the any other virtual warehouses. This makes each virtual warehouse is independent and shows no impact on the other virtual warehouses in case of any failover.
95.What is the Cloud Services layer in a Snowflake architecture?
The Cloud Services layer consists of a set of services that coordinates a multiple tasks across the Snowflake platform. All these services tie together and work with the great co-ordination to process user requests, from login to a query dispatch. This layer also executes compute instances assigned by Snowflake from cloud manager.
- Metadata management.
- Infrastructure management.
- Access control.
- Optimization and query parsing.
96. Does Snowflake have a coding?
97. Why is a Snowflake so popular?
- Snowflake’s popularity as a top cloud data warehousing solution stems from the fact that it covered a wide range of areas, including business intelligence, data integration, advanced analytics, security and governance.
- It supports a programming languages like Go, Java, Python, and others. It has an out-of-the-box features like storage and computation isolation, on-the-fly scalable compute, data sharing, data cloning, and more.
98. Are Snowflake developers in the demand?
The demand for a Snowflake professionals is at an all-time high, and it’s only getting higher. In recent years, the industry has an experienced tremendous growth in Snowflake’s job postings. It is expected that there will be an even more opportunities in the near future.
99. What are the skills of a Snowflake developer should possess?
- Firm grasp of a basics of Snowflake.
- Statistical skills.
- Competent a programming knowledge.
- Data analysis and manipulation abilities.
- Data visualisation skills .
- A systematic and structured approach towards a problem-solving.
- Passion for the learning.
100. What are the benefits of using a Snowpipe?
- Real-time insights
- Ease of use
- Zero Management
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