Building Data Foundation on: Snowflake for Data Warehousing

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The Snowflake event held on 14th January 2024 covered an in-depth understanding of Snowflake, a cloud-based data warehouse platform, along with its architecture, functionalities, and use cases. The day was divided into four structured sessions, each focusing on different aspects of Snowflake and data warehousing.

Session 1: Introduction to Data Warehousing and Snowflake (9:00 AM – 11:00 AM)

The first session began with an introduction to the concept of data warehousing and the distinction between structured and unstructured data. The key focus was on Snowflake, a cloud-based data warehouse management platform capable of handling large-scale data efficiently.

Key Highlights:

  1. Snowflake Overview:
    • Cloud-based architecture that supports multi-cloud integration.
    • Processes large-scale data with features like scalability, elasticity, and cost efficiency.
  2. Snowflake Architecture:
    • Consists of three main components: Cloud Services, Query Processing, and Storage.
  3. Benefits of Snowflake:
    • Cloud-based architecture enabling data accessibility anywhere.
    • Elasticity and scalability for dynamic workloads.
    • Concurrency allowing multiple users to access data simultaneously without performance degradation.
    • Data sharing across organizations (internal or external).
    • Time Travel feature to track and view previous transactions and changes.
    • Cost-efficiency with a pay-as-you-go model.
  4. Additional Topics:


Virtual warehouse sizes, multi-clustering, and scaling policies.

    • Cold and hot backups were discussed, emphasizing their importance for data recovery.
    • Roles in Snowflake were briefly introduced.

The session concluded with a walkthrough of Snowflake and a practical demonstration of creating a database and tables using SQL queries.

Session 2: Data Loading and Transformation (11:10 AM – 12:40 PM)

The second session focused on understanding the parameters of the COPY function and the process of loading data into Snowflake using staging.

Key Highlights:

  • Detailed explanation of the COPY function and its parameters.
  • Overview of loading data from AWS staging.
  • Introduction to data transformation techniques within Snowflake.

Session 3: JSON Data Handling in Snowflake (1:30 PM – 3:00 PM)

This session emphasized working with JSON files in Snowflake.

Key Highlights:

  • Loading JSON files into Snowflake.
  • Parsing JSON files to extract and manipulate data effectively.

Session 4: Assignments and Types of Data Warehouses (3:10 PM – 4:30 PM)

The final session provided participants with assignments and introduced the different types of data warehouses.

Key Highlights:

  • Practical tasks to reinforce the concepts learned throughout the day.

Overview of various data warehouse types, including enterprise, operational, and cloud data warehouses. 

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