Data analysis is a valuable tool that companies can apply to maintain a competitive edge. In this Acceleration Case Study, learn how The Home Depot transitioned to a cloud-based data warehouse to improve data management with Google Cloud‘s BigQuery data management platform. With the shift in strategy, The Home Depot can better integrate its business operations to manage performance as well as empower workers to meet customer demand.
Business Challenge – Managing an Ever-Growing Amount of Data
The Home Depot is one of the most popular home improvement store chains, with more than 2,200 stores and 50,000 products. Focusing on data analysis continuously plays a vital role in the company’s success. Its use cases include creating detailed sales forecasts, resupplying inventory, and maintaining performance scorecards.
- They set the following goals:
- Improve business operations
- Better manage performance
- Empower workers
- Meet customer demand
- Manage performance, cost, and data priorities
Maintaining a competitive edge in today’s business environment requires a greater data-driven approach than was possible with The Home Depot’s legacy technology. Because of all the data required for analysis, its on-premise data warehouse was under much stress. The rapid growth of data created significant challenges in performance, cost, and managing data priorities. Adding more capacity for all the data required a lot of planning and testing.
And, capacity was reaching its limit, which impacted performance. It also became difficult to maintain such data-intensive workloads. So, The Home Depot needed a better way to keep up with these demands, as the capacity refresh cycles continued to shrink. Meanwhile, the need for data continued to grow rapidly.
- They aimed to accomplish these goals by:
- Implementing a data-driven approach
- Focusing on data analysis
- Using cloud technology to empower employees
- Using AI and online commerce to meet customer needs
The company decided to implement a data-driven approach to maintain a competitive edge. By using artificial intelligence and online commerce, the company could not only meet customer needs but also improve security.
Technology Solution – Using BigQuery for Data Warehouse Management
The Home Depot needed a cloud solution to keep up with its ever-growing data demands. The retailer selected Google Cloud’s BigQuery as a solution for its data warehouse. BigQuery is a scalable, “serverless” cloud data warehouse.
With BigQuery, capacity can be easily added, so service interruptions can be avoided. Standard SQL support and serverless capabilities make the cloud data warehouse relatively easy to use without complicated system administration. Also, thanks to identity and access management, The Home Depot had the flexibility to create separate Google Cloud projects without causing interference with other teams.
BigQuery’s fixed-rate monthly pricing model made it easy to stay within budget without worrying about any variable costs. At the same time, any unused capacity is available for other business use, a source of computing power without additional expenses.
The Results
The Home Depot’s legacy data warehouse consisted of 450 terabytes of data, while the BigQuery data warehouse handles more than 15 petabytes. The much larger database gives The Home Depot more flexibility for improved decision-making.
Here are some of the results of using Google Cloud’s BigQuery:
Supply Chain Use Case
On-Premise Time – 8 Hours, BigQuery Time – 5 Minutes
Finance Use Case
On-Premise Time – 14 Days, BigQuery Time – 3 Days
Customer Order Use Case
On-Premise Time – 9 Hours, BigQuery Time – 12 Minutes
Store Performance Dashboard Use Case
On-Premise Time – 51 Seconds, BigQuery Time – 2 Seconds
Sales Analysis Use Case
On-Premise Time – 120 Minutes, BigQuery Time – 20 Minutes
Data analysts at The Home Depot can now run more complex workloads than were possible before. And engineers have adapted BigQuery to monitor, analyze, and utilize application performance data in real-time throughout its stores and warehouses.
