In this Acceleration Case Study, learn how The Home Depot, a home improvement chain, transitioned to a cloud-based data warehouse to improve business operations. The company needed to implement a data-driven approach to maintain a competitive edge. Recognizing a need to focus on data analysis, The Home Depot determined it needed a solution to better integrate its business operations to manage performance, empower workers, and meet customer demand. Read how The Home Depot overcame its data warehouse challenges by implementing Google Cloud’s BigQuery.
Business Challenge – Managing an Ever-Growing Amount of Data
The Home Depot is one of the most popular home improvement store chains. It hosts over 2,200 stores and more than 700,000 products. Focusing on data analysis continuously plays a vital role in the company’s success. This is essential, whether it involves creating detailed sales forecasts, resupplying inventory throughout the supply chain, or maintaining performance scorecards.
However, to remain competitive in today’s business environment requires an even greater data-driven approach that’s not possible to use with legacy technology. The Home Depot needed to find a way to better integrate its business operations. For example, this may include its tool rental services.
Developing a way to empower workers was critical. This can even involve its store associates using the cloud or an ever-expanding data analysis staff. Using artificial intelligence and online commerce was important in better meeting customers’ needs while also improving security.
Because of all the data required for analysts, the existing on-premise data warehouse was under much stress. The rapid growth of this data created significant challenges in managing performance, cost, and data priorities. Adding more capacity for all the data required a lot of planning and testing. For example, one case for increasing capacity took six months to plan. Furthermore, it resulted in a service outage for three days to implement.
However, capacity was again reaching its limit within the next year. This impacted performance as well as made it difficult to maintain such data-intensive workloads. The Home Depot needed to find a better way to keep up with these demands, as the capacity refresh cycles continued to shrink while the need for data continued to grow rapidly.
Technology Solution – Using BigQuery for Data Warehouse Management
The Home Depot needed a cloud solution to keep up with its ever-growing data demands for maintaining business operations. After extensive research, The Home Depot selected Google Cloud‘s BigQuery as a solution to handle its data warehouse on the cloud. BigQuery is a scalable and serverless data warehouse offering better infrastructure agility and analytic features to gain insights on business operations.
Once capacity was added, there were no service interruptions. It only took a week to implement this cloud technology. Standard SQL support makes it easy to use, as it doesn’t require any complicated system administration. Due to Identity and Access Management features, The Home Depot had the flexibility to create separate Google Cloud projects without causing any interference with other teams.
The fixed-rate monthly pricing model of BigQuery made it easy to stay within budget without worrying about any variable costs. The remaining capacity not being used for a project remained available for business use, which provided substantial computing power without any additional expenses.
The Home Depot’s legacy data warehouse consisted of 450 terabytes of data, while the BigQuery data warehouse provides more than 15 petabytes. Ultimately, this gives The Home Depot much more flexibility in using data to improve decision-making by using new datasets to boost its operations further.
Here is an overview 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 perform much more complex workloads that weren’t possible before making the switch to Google Cloud’s BigQuery. Engineers have also adapted BigQuery to monitor, analyze, and utilize application performance data in real-time throughout its stores and warehouses. BigQuery is just one way that Google Cloud is helping The Home Depot achieve business results every day.