Data Warehousing for Realtime Pipelines

Introduction

In today's fast-paced world, decision-making can't wait. Businesses need to react instantly to changing situations, especially when dealing with high-volume transactions. Imagine managing an online retail store where thousands of transactions are happening every minute. Relying on yesterday's data for pricing adjustments or inventory management means you're already a step behind.

This is where real-time data warehousing comes into play, enabling businesses to make decisions based on what is happening right now, rather than on outdated information.

The Problem with Traditional Data Warehouses

Traditional data warehouses were built around periodic updates—think of overnight batch jobs processing data to refresh reports by morning. This worked well when decisions could afford to wait. However, the modern business environment demands up-to-the-second insights to remain competitive.

About This Project

This project explores an example of a real-time data warehouse architecture, using tools and technologies in the modern data stack that one can utilize. By understanding how to implement a real-time data warehouse, you will gain insights into creating a responsive data platform for real-time analytics workload suitable for today's dynamic analytical landscape.