Yellowfin > Case Studies > Digital Planet Enhances Data Analytics Performance with Yellowfin and Exasol

Digital Planet Enhances Data Analytics Performance with Yellowfin and Exasol

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 Digital Planet Enhances Data Analytics Performance with Yellowfin and Exasol - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Education
  • Retail
Applicable Functions
  • Procurement
  • Warehouse & Inventory Management
Use Cases
  • Inventory Management
  • Picking, Sorting & Positioning
Services
  • Cloud Planning, Design & Implementation Services
  • Data Science Services
The Challenge
Digital Planet wanted to provide a better data analytics experience for its customers, with full self-service reporting capabilities. However, it had substantially grown its data warehouse over many years of operations, and the gradual expansion of its business soon led to performance degradation.
The Customer
About The Customer
Digital Planet is a B2B2C enterprise that sources and delivers tailored technology and education retail deals to corporate customers such as banks and telcos. Its partner network consists of educational institutions and leading technology brands such as Microsoft.
The Solution
Digital Planet decided to expand upon its usage of Yellowfin analytics to align with its move from SQL to a more scalable data environment that could support the latest self-service BI for its clients. With assistance from AIGS and Yellowfin, Digital Planet formed a partnership with Exasol, a high-performance analytical database software company, to increase data warehouse performance through hosting its data warehouse in the cloud.
Quantitative Benefit
  • The improvements in data load and refresh times have allowed Digital Planet to enhance its data analytics capabilities, measure key performance indicators more effectively, and share richly visualized data stories with its customers. It has also optimized its data warehouse costs and refresh performance from hours to minutes, resulting in significant cost savings.

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