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Globalmart Building Enterprise Data Foundation on Snowflake

20 Inputs
2 Hours 30 Minutes
Intermediate
scenario poster
Industry
e-commerce
Skills
data-wrangling
data-storage
Tools
snowflake

Learning Objectives

Design and implement a Silver Layer data model within Snowflake to refine raw, messy data into a clean, consistent, and integrated format.
Efficiently extract and transform semi-structured data stored in VARIANT columns within Snowflake, converting raw event logs into structured analytical tables.
Master data cleansing and standardization techniques using Snowflake SQL functions (e.g., TRIM, INITCAP, LOWER, REPLACE, REGEXP_REPLACE) for various data types
Implement data quality and validation checks directly within SQL to ensure the reliability and usability of transformed data

Overview

GlobalMart, a rapidly growing online store, found its quick success caused a new problem. Their old computer systems couldn't handle the huge amount of data coming in. This left them with thousands of daily sales records that were messy and hard to use. Even with all this information, GlobalMart couldn't find the answers they needed to keep growing.

This project shows GlobalMart's important change. It explains how they used Snowflake to turn a flood of data into a powerful tool for understanding their business. Guided by their Data Engineer Vinay and Senior Architect Rahul, you will learn how to build a strong "Silver Layer"—this is the key step that changes raw data into useful information.

You will learn how to:

  • Set up a flexible "Silver Layer" on Snowflake, built to ensure data is good quality and consistent.
  • Become skilled at cleaning and fixing data: You'll learn to make customer names the same, check emails and phone numbers, and get addresses into the right format.
  • Apply business rules to raw data, creating useful groups for things like where customers are, how orders are placed, types of products, and reasons for returns.
  • Change disorganized information into clear, dependable data that forms the base for all future analysis.

This project is about more than just changing data. It's about making data trustworthy. This helps businesses make smart, informed decisions. You'll learn the vital steps to turn messy, unusable information into a reliable asset, getting it ready for the detailed reports and analysis that happen in the "Gold Layer."

If you work with data and want to build dependable data systems, and learn how to refine data carefully, this project will give you the skills. You'll learn to create the clean and consistent data base that every growing business truly needs.

Prerequisites

  • Experience with core Snowflake concepts including databases, schemas, and virtual warehouses.
  • Basic understanding of data warehousing principles, particularly the roles and objectives of the Staging (Bronze), Integration (Silver), and Consumption (Gold) data layers.
  • Familiarity with Snowflake's rich set of built-in SQL functions for string manipulation (e.g., TRIM, UPPER, INITCAP, REPLACE), date and time operations (e.g., DATEDIFF, DATEADD, YEAR), and data type conversions (e.g., TRY_TO_NUMBER, CAST).
  • Knowledge of handling flexible schemas and extracting nested data structures using Snowflake's VARIANT data type.