Snowflake Project 1: Warehouse Setup and Basics

Project Overview

This project focuses on the fundamental setup of Snowflake. It covers creating a virtual warehouse, setting up databases and tables, inserting sample data, and loading external data from Amazon S3 into Snowflake. The aim is to build a strong foundation for future Snowflake projects involving automation, data ingestion, and analytics.

Prerequisites

• Active Snowflake account
• Access to Snowflake Web UI or SnowSQL
• AWS credentials with permissions to access the provided S3 bucket

Tasks Performed

TASK 1: Virtual Warehouse Setup

• Created a warehouse named demo
• Configured it as a Standard type, X-Small size
• Enabled auto-resume and auto-suspend (set to 5 minutes) for cost efficiency

TASK 2: Database and Table Creation

• Created a database named sales_db
• Designed a table named sales in the public schema
• Inserted a few sample records to validate the setup
• Queried the table to ensure data retrieval worked correctly

TASK 3: Data Loading from S3

• Created a new database named sales_s3_db
• Designed a table named sales_data_s3 with customer and sales details
• Loaded data from the S3 bucket snowflake-hands-on-data/sample_data_basic/sales_sample_data.csv
• Applied configurations like comma delimiter and skipping the header row
• Verified that all rows were ingested successfully

Real-World Relevance

• Warehouse Setup ensures queries run efficiently and cost effectively
• Databases and Tables provide structured environments for organizing transactional and analytical data
• S3 Data Loading reflects a common enterprise use case where raw data is stored in cloud storage and ingested into Snowflake for reporting and BI