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Digital Planet Enhances Data Analytics with Cloud and Yellowfin

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 Digital Planet Enhances Data Analytics with Cloud and Yellowfin - 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, a B2B2C enterprise, was facing challenges with its data warehouse performance due to its gradual expansion over the years. The company wanted to provide a better data analytics experience for its customers, with full self-service reporting capabilities. However, the performance degradation of its data warehouse limited its ability to offer additional data-related services to its customers during office hours. Data refresh was done every hour and updates could take as long as 20 minutes, slowing down the reporting environment for customers. As Digital Planet was looking to enhance its technology offering with both self-service reporting and embedded analytical reporting for its customers, it identified the clear need to optimize its current environment first. This required implementing the right analytics and business intelligence solutions in place that could fulfil all its various data-related objectives.
The Customer
About The Customer
Founded in 1999, Digital Planet is on a mission to enrich the lives of all South Africans with greater access to education and technology. As a B2B2C enterprise with an ethos built on partnership, it sources and delivers tailored technology and education retail deals with full service distribution directly to corporate customers such as banks and telcos, which these organizations can then offer to clients as part of a seamless value-add experience. The company manages all touch points from product to client to consumer, such as sales, marketing and customer tech support, procurement, stock and call center order management, delivery and warranty. 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 identified and evaluated its options and decided to form a partnership with Exasol, a high performance analytical database software company and global partner of Yellowfin, in order to increase data warehouse performance through hosting its data warehouse in the cloud. Exasol took the time necessary to take Digital Planet’s developers through its product and how it could greatly improve warehouse performance, before providing a hands-on walkthrough of its setup and support through the initial development build work. The joint effort between Exasol and Yellowfin helped Digital Planet understand how Exasol could align with its needs – and eventually deploy its solution in Microsoft Azure successfully.
Operational Impact
  • The increased performance of its data warehouse has modernized the customer experience, by enabling the creation of a self-service customer portal and embedding Yellowfin for data analytics into its client portal. Digital Planet now uses Yellowfin’s embedded analytics and data visualizations to more effectively measure various contractual obligations. This includes the measurement of important key performance indicators (KPIs), such as fulfillment rate (measure of orders received vs delivered) and the duration of various important sub processes. Digital Planet is also leveraging data storytelling capabilities such as Yellowfin Present to share more widely accessible, richly visualized data stories to its customers. The company plans to experiment further with Yellowfin and Exasol’s high-performance database, as the better data load and refresh times allow for more flexibility to experiment with Yellowfin’s analytics suite.
Quantitative Benefit
  • Reduced initial data load times from 2 hours to 7 minutes, an improvement of 1700%
  • Reduced refresh loads from 20 minutes per hour to under 2 minutes, an improvement of 1000%
  • Significantly increased the number of users of Yellowfin to offer self-service reporting to more of its customers overall

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