The Home Depot moves its data to the cloud
Global home-improvement chain The Home Depot (THD) has driven much of its worldwide success through data analysis. From sales forecasts to performance scorecards and replenishing its inventory through its supply chain network.
However, as it looked to remain the world’s leading home-improvement firm, THD had to modernise its focus on data.
It required a cloud platform that could properly integrate its related businesses, while better equipping its teams, such as its data analysis staff and store associates. THD also sought to utilise e-commerce and AI to improve customer experience, while also solidifying its security.
The company’s on-premises data warehouse was proving limited in dealing with the data required for analytics and was coming under significant stress as a result of the increasingly complex use cases data analysts were utilising.
This created problems in managing priorities and cost as well as optimizing performance, while adding capacity to the data warehouse was a major effort that sometimes required months of planning and resulted in a service outage.
Following a long consideration process, THD chose to migrate its data infrastructure to Google Cloud’s BigQuery.
BigQuery provided a solution to many of THD’s needs, being scalable, more cost-effective, having a more agile infrastructure and analytics capabilities that allowed it to drive better insights.
It allowed THD to add capacity quickly and without any loss of service, while products such as Identity and Access Management allowed it to create numerous Google Cloud projects without different teams interfering with one another or accessing protected data.
Overall, BigQuery allowed THD to make significant improvements in performance. For instance, prior to migrating, supply chain use case through the on-premises infrastructure took up to 8 hours. Following the move to BigQuery, this was cut to just 5 minutes, a reduction in time of 99 per cent.
With the migration complete, THD analysts now execute more complex, demanding workloads than would have been possible before. While engineers have adapted BigQuery to allow them to monitor, analyze, and act on application performance data across all stores and warehouses in real time.
