--- title: Cloud Optimization Tool Case Study | Envisor description: Our client saved 70% on Azure costs while decreasing ETL load times using Envisor. Read the case study. --- [Skip to content](https://envisor.io/customer-success/senturus#main-content) [![Envisor, The open FinOps platform](https://envisor.io/hubfs/Envisor%20tagline%20logo.svg)](https://envisor.io?hsLang=en) - Platform Show submenu for Platform - [Why Envisor](https://envisor.io/why-envisor) - [FinOps Analytics](https://envisor.io/analytics) - [Architecture](https://envisor.io/architecture) - [FOCUS Native](https://envisor.io/focus-normalization) - [Ad Hoc Analytics](https://envisor.io/data-blending) - Solutions Show submenu for Solutions - [CIO - CTO](https://envisor.io/solutions-for-cio-cto) - [Core FinOps](https://envisor.io/solutions-for-core-finops) - [Engineering](https://envisor.io/solutions-for-engineers) - [Finance](https://envisor.io/solutions-for-finance) - Resources Show submenu for Resources - [Blog](https://envisor.io/blog) - [News](https://envisor.io/news) - [Events](https://envisor.io/events) - [DCU Calculator](https://envisor.io/dcu-calculator) - Company Show submenu for Company - [About Us](https://envisor.io/about-us) - [Careers](https://envisor.io/careers) Open main navigation Close main navigation - Platform Show submenu for Platform - [Why Envisor](https://envisor.io/why-envisor) - [FinOps Analytics](https://envisor.io/analytics) - [Architecture](https://envisor.io/architecture) - [FOCUS Native](https://envisor.io/focus-normalization) - [Ad Hoc Analytics](https://envisor.io/data-blending) - Solutions Show submenu for Solutions - [CIO - CTO](https://envisor.io/solutions-for-cio-cto) - [Core FinOps](https://envisor.io/solutions-for-core-finops) - [Engineering](https://envisor.io/solutions-for-engineers) - [Finance](https://envisor.io/solutions-for-finance) - Resources Show submenu for Resources - [Blog](https://envisor.io/blog) - [News](https://envisor.io/news) - [Events](https://envisor.io/events) - [DCU Calculator](https://envisor.io/dcu-calculator) - Company Show submenu for Company - [About Us](https://envisor.io/about-us) - [Careers](https://envisor.io/careers) - [CONTACT US](https://envisor.io/contact-us) [CONTACT US](https://envisor.io/contact-us?hsLang=en) # Senturus saved 70% on cloud costs while decreasing ETL load times Using Envisor, Senturus was able to scale to the optimal Azure capacity level required to meet their ETL database processing needs. By dynamically scaling Azure to meet peak and low demand times at the optimal service level, they saw data import performance accelerate by 85% and overall costs decrease by 70%. ![cloud-building](https://envisor.io/hs-fs/hubfs/cloud-building.jpg?width=808&height=439&name=cloud-building.jpg "cloud-building") ## Challenge Senturus relies on 50 Azure SQL databases to address the needs of its businesses. Like most organizations running a cloud environment, the company was paying for capacity they were not using. They had sized their Azure resources to accommodate peak demand, but that capacity remained idle for large portions of the day. Take the example of one of their ETL databases. Senturus would run daily data imports from external web apps into an Azure SQL database. To meet delays in the data import process, admins responded in the typical manner, bumping up the Azure SQL database performance level to speed up the data imports. The increased service level solved the performance issue but wasted money since the database would remain idle for the rest of the day. ## Solution ![](https://envisor.io/hubfs/envisor-case-studay-image-1.png) Using Envisor, Senturus is now able to accurately understand their server utilization, match it to the optimum required capacity level, and dynamically scale the server to meet demand. Senturus looked at their Azure SQL database, which was running at an S2 level for the entire 24-hour period. Envisor revealed that the database was under-provisioned for a couple of hours early each morning during the ETL load and idle (over-provisioned) the rest of the day. With this insight, Senturus determined that scaling to the S4 tier, while the most expensive level, would be the most cost-effective. Using Envisor, they set the Azure SQL database to scale up during the ETL loads when more performance is required, and back down when it needs to only be generally available. ## "Using Envisor, we saw data ingestion performance accelerate by 85% and overall costs decrease by 70%." Senturus ## Benefits Envisor allowed Senturus to rethink their computational performance needs and dynamically manage their Azure capacity. Moving to the S4 tier gives them the computing power needed to meet peak demand and also decrease the load time. For this one ETL database, Senturus has seen impressive cost savings and performance improvements: - Data import performance accelerated by 85%. - Users receive data 90 minutes earlier than previously. - Overall costs decreased by 70%. Envisor can reduce costs and improve performance for other cloud resources as well. ## About our client Senturus is a nationwide business intelligence consulting, training and software firm. [Follow us on LinkedIn](https://www.linkedin.com/company/79365137) [Follow us on YouTube](https://www.youtube.com/@envisor-cloud/featured) --- [![Envisor, The open FinOps platform](https://envisor.io/hubfs/Envisor%20tagline%20logo.svg "Envisor, The open FinOps platform")](https://envisor.io/?hsLang=en) 533 Airport Blvd., Burlingame, CA 94010 © 2026 Envisor [Terms](https://envisor.io/terms-of-use?hsLang=en)[of](https://envisor.io/terms-of-use?hsLang=en)[Use |](https://envisor.io/terms-of-use?hsLang=en)[Privacy Policy](https://envisor.io/privacy-policy?hsLang=en)