Establishing the Reporting Layer at GlobalMart

Learning Objectives

Design and implement a comprehensive reporting layer within Snowflake focused on transforming customer and sales data into actionable insights.

Apply advanced SQL techniques using Snowflake SQL (e.g., complex aggregations, subqueries, and grouping) to build robust analytical reports.

Build foundational customer analytics and segmentation models to reveal purchasing patterns, calculate customer value (like Average Order Value), and support targeted marketing strategies.

Utilize Snowflake's view capabilities to pre-compute and optimize data access for frequently used analytical queries.

Develop custom SQL functions to implement dynamic business rules, such as assigning customer-specific promotions based on their behavior.

Overview

GlobalMart started as a small e-commerce startup with ambitious goals and a lean team. Within just a few years, this company evolved from processing dozens of daily orders to managing thousands of transactions across multiple regions. However, rapid growth brought an unexpected challenge: explosive data growth that overwhelmed their on-premises infrastructure. The solution was clear—GlobalMart needed to migrate to the cloud, with Snowflake as their platform of choice.

Vinay, GlobalMart's Data Engineer, collaborated with Rahul, the Senior Architect, to lead this critical migration. After weeks of meticulous planning and execution, they reached a significant milestone: all of GlobalMart's historical data was successfully migrated into Snowflake.

GlobalMart's data journey doesn't end with organized data; it's the foundation for what's next. After building their staging and integration layers, Vinay and Rahul now face the crucial challenge: transforming perfectly prepared data into actionable insights for customer behavior and sales.

This scenario guides you through building GlobalMart's "Gold Layer"—the comprehensive reporting foundation in Snowflake. It’s about creating the analytical backbone that will drive growth through a deeper understanding of customers.

You will gain expertise to:

Design and implement a reporting layer focused on customer and sales data.
Apply advanced SQL techniques, including complex aggregations and subqueries, for robust analytical reporting.
Build customer analytics that reveal purchasing patterns, enable value-based segmentation (like Average Order Value), and support targeted marketing.
Utilize Snowflake views to optimize performance for key analytical queries.
Develop SQL Functions for business rules, such as assigning dynamic promotions based on customer behavior.

When you finish this project, you'll have created a practical system for analyzing data. It will provide insights to help you understand what customers need and take specific actions. You'll learn to write data queries and structure data so it's useful for business. This project helps you build the part of a data system that allows companies to work more effectively with their customers

Prerequisites

Understanding of core Snowflake concepts, including the purpose and usage of databases, schemas, and virtual warehouses.
Familiarity with basic Snowflake SQL interaction, such as USE DATABASE and USE SCHEMA commands, and navigating its interface (UI/SnowSQL).
A strong grasp of data warehousing principles, specifically the distinct roles and objectives of the Staging (Bronze), Integration (Silver), and Consumption (Gold) data layers.
Knowledge of dimensional modeling concepts, including the purpose of fact and dimension tables, and the use of primary, foreign, and surrogate keys.
Proficiency in standard SQL commands, such as SELECT, FROM, JOIN, WHERE, and GROUP BY, along with common aggregate functions like SUM, AVG, COUNT, and ROUND.
Experience with advanced SQL techniques, including conditional logic using CASE statements and the application of subqueries for complex data retrieval. Basic awareness of SQL data types like VARCHAR and NUMERIC is also expected.
Ability to create and utilize Snowflake Views, for simplifying complex queries, organizing data, and optimizing presentation.
Understanding of Snowflake's User-Defined Functions (UDFs) for encapsulating reusable business logic