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Scaling Data for Growth at Globalmart

24 Inputs
2 Hours
Intermediate
scenario poster
Industry
e-commerce
Skills
data-wrangling
batch-etl
data-understanding
Tools
azure
snowflake

Learning Objectives

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 as its data grew rapidly. Their on-premises system could no longer keep up, leading to a bold decision: move to Snowflake, a cloud platform designed for scalability and speed.

In this project, you’ll follow GlobalMart’s journey to the cloud, learning how to:

  • Seamlessly migrate data from on-premises servers to the cloud

  • Design a scalable data system for growing businesses

  • Overcome challenges like data security, downtime, and consistency

  • Implement Snowflake to manage large-scale data

As GlobalMart’s success spreads, the pressure mounts. Vinay, the Data Engineer, is tasked with migrating data for marketing, sales, finance, and more — ensuring the business’s data is unified and ready for decision-making.

By the end of this project, you’ll have the skills to handle cloud migrations and scale data infrastructures for fast-growing businesses. Ready to take the next step in data transformation? This project is your gateway.

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