Case Study: Agoop optimizes data processing and cuts reporting costs with Microsoft Azure SQL Data Warehouse (Microsoft Azure)

BI provider optimizes data processing with Azure SQL Data Warehouse

Agoop, a Tokyo-based business intelligence provider that combines location information with big data, faced rising operational costs and heavy manual effort for a daily reporting service. Its legacy database and multiple linked systems could not keep up with large batch workloads, so the company needed to renew or migrate its infrastructure to reduce costs, lower management overhead, and make better use of its data.

Agoop built its database infrastructure on Azure SQL Data Warehouse (development starting 2015, production June 2016) to enable massively parallel processing and better integration of pre-ETL data, shifting from ETL to ELT. The move reduced data-processing costs and labor, decreased operational management time through system integration and cloud scalability, increased the practical value of stored data, and set the stage for future links to Azure Machine Learning, Power BI, and overseas report migrations.

Agoop