Establishing Data Migration Framework at GlobalMart

20 Inputs

2 Hours

Advanced

Industry

e-commerce

Skills

data-wrangling

batch-etl

data-understanding

Tools

snowflake

azure

Learning Objectives

Configure Azure Data Lake Storage integration with Snowflake

Create and manage external stages for accessing cloud-based data files

Perform schema discovery on unknown data files using Snowflake's INFER_SCHEMA functionality

Design staging tables following cloud data warehouse best practices

Execute bulk data loads using COPY INTO commands

Create comprehensive audit tables to track data loading metrics and success rates

Overview

GlobalMart, a fast-growing e-commerce company, faced a challenge — their old data system couldn’t keep up with the rapid growth. As their data volumes increased, it became clear that the on-premises infrastructure was holding them back. The solution? Moving to Snowflake, a cloud platform designed for speed and scalability.

In this project, you’ll follow GlobalMart’s journey as they transition to the cloud. You’ll learn how to:

Migrate data from on-premises servers to the cloud with ease
Set up a scalable data system that can grow with the business
Tackle challenges like data security, downtime, and data consistency
Implement Snowflake to manage large-scale data efficiently

This project isn’t just about technology — it’s about transforming how businesses handle data to make smarter, faster decisions.

If you want to gain hands-on experience with cloud migrations and discover how businesses scale using Snowflake, this project is your perfect starting point.

Prerequisites

Solid understanding of SQL for writing complex queries, transformations, and validation scripts.
Experience with Snowflake data warehouse concepts and schema design
Familiarity with cloud storage platforms such as AWS S3, Azure Blob Storage, or GCP Storage.
Knowledge of data ingestion techniques for bulk loading in Snowflake