How GoDaddy transformed its analytics with Amazon Quick
In this post, you will learn how GoDaddy migrated from their legacy business intelligence (BI) tool to Amazon Quick. This was a two-year transformation that delivered results across every dimension of the business: 15,000 hours saved annually, 50% reduction in dashboard count, rendering times cut to under 5 seconds, and AI-powered self-service analytics now accessible to every employee.
GoDaddy, a leading domain registrar and web hosting provider, serves over 20 million customers and manages approximately 82 million domain names. To keep up with its scale, the company needed a reliable analytics infrastructure. However, their existing analytics environment was struggling under the weight of thousands of dashboards, rising infrastructure costs, and long report loading times, often exceeding 15 minutes.
This prompted GoDaddy to transform its analytics approach with Amazon Quick Sight, a serverless, auto-scaling, and cost-effective BI solution.
The transformation journey began in mid-2023 with a formal evaluation of the BI landscape. Amazon Quick Sight stood out due to its native integration with AWS services such as Amazon Redshift, Amazon S3, and Amazon RDS, eliminating the need for a separate BI stack and reducing infrastructure overhead. Its pay-as-you-go pricing model provided a more predictable and cost-effective solution for an enterprise of GoDaddy's size.
Lastly, Quick Sight's built-in machine learning capabilities, including anomaly detection, forecasting, and natural language querying, opened up the possibility of democratized, self-service analytics across the organization.
The migration process took roughly two years, starting with a soft launch in the third quarter of 2023. Foundational setup included establishing AWS integrations, building governance frameworks, migrating the first wave of dashboards, and onboarding users. By December 2025, the legacy BI tool was retired, and Amazon Quick Sight became GoDaddy's primary BI solution.
This migration led to significant improvements in performance and usability, with dashboard rendering times reduced to under 5 seconds, a 15,000-hour annual productivity gain, a 50% reduction in dashboard count, and AI-powered self-service analytics accessible to every employee.
Written by urgent.news from AWS Machine Learning's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
This story
This is one outlet's version. Read the fullest account.
