Introduction to Snowflake and its use cases

In this recipe, we will learn about Snowflake. We will also learn about the use cases of Snowflake.

Recipe Objective - Introduction to Snowflake and its use cases?

The Snowflake is a widely used service and is defined as a service data storage and entirely cloud-based analytics service. Data warehouse as a Software-as-a-Service (SaaS). Snowflake database is an architecture and a completely new SQL database engine designed to work with cloud infrastructure. Unlike traditional databases, users do not need to download and install Snowflake to use it; instead, users must create an account online, which grants them access to the web console, from which they create the database, schema, and tables. Access the database and tables using the Web console, ODBC, JDBC, and third-party connectors. Though the underlying architecture is different, it shares the same ANSI SQL syntax and features, making learning Snowflake simple and quick if users have a SQL background. Snowflake is built on the cloud infrastructures of Amazon Web Services, Microsoft Azure, and Google. Because there is no hardware or software to choose, install, configure, or manage, it is ideal for organisations that do not wish to devote resources to the setup, maintenance, and support of in-house servers. Data can also be easily moved into Snowflake using an ETL solution like Stitch. What distinguishes Snowflake is its architecture and data-sharing capabilities. Users can use and pay for storage and computation separately thanks to the Snowflake architecture's ability to scale storage and compute independently. Furthermore, the sharing functionality enables organisations to quickly share governed and secure data in real-time. With big data, Snowflake's architecture allows for similar flexibility. Snowflake decouples storage and computes functions, so organisations with high storage requirements but a low need for CPU cycles, or vice versa, don't have to pay for an integrated bundle that requires them to pay for both. Users can scale up or down as needed, paying only for the resources they use. Storage is charged in terabytes per month, while computation is charged per second.

Benefits of Snowflake

  • Because the cloud is elastic, users can scale up their virtual warehouse to take advantage of extra compute resources if they need to load data faster or run a high volume of queries. After that, users can downsize the virtual warehouse and only pay for the time they used and thus offering Performance and Speed. Users can combine structured and semistructured data for analysis and load it directly into a cloud database without first converting or transforming it into a fixed relational schema. Snowflake optimises data storage and querying automatically and thus offers structured and semistructured data storage and support. When too many queries compete for resources in a traditional data warehouse with a large number of users or use cases, users may encounter concurrency issues (such as delays or failures). Snowflake's unique multicluster architecture addresses concurrency issues: queries from one virtual warehouse never affect queries from another, and each virtual warehouse can scale up or down as needed. Data analysts and data scientists can get what they need right away, without waiting for other loading and processing tasks to finish and thus offering Ease of access and concurrency. Snowflake's architecture allows Snowflake users to share data. It also enables organisations to share data with any data consumer, whether or not they are a Snowflake customer, via reader accounts that can be created directly from the user interface. This feature enables the provider to set up and manage a Snowflake account for a customer and thus offers seamless data sharing capabilities.

System Requirements

  • Any Operating System(Mac, Windows, Linux)

This recipe explains Snowflake and uses cases of snowflakes.

Use cases of Snowflake

    • It provides amazing storage facilities.

Data storage in the cloud is more scalable and generally less expensive than on-premise data storage thus, Snowflake is preferred.

    • It provides reporting as its use case.

With the aid of data warehouses, the user's team can produce more business reporting more quickly and broadly. Restructuring the data to make it more valuable and understandable for business users is also made simpler by moving to the cloud.

    • It provides analytics as its use case.

Users can perform data analysis using Snowflake at any scale to obtain the insights users require. Users will improve operational business applications by integrating them into their larger systems. Take the customer relationship management (CRM) programme as an illustration.

What Users are saying..

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Ed Godalle

Director Data Analytics at EY / EY Tech
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I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills... Read More

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