Keio University Injects Vital Research Data Directly into Tableau with CData

When visualizing and analyzing healthcare-related data in Tableau, the university adopted the CData Driver for XML to standardize and simplify their data acquisition and reduce development hours.

Direct Access to Data
Keio University no longer loses time manually transforming data, as CData allows Tableau to read XML data as if it were natively compatible.
No Code to Install and Run
CData offered Keio University a drop-in solution for connectivity to XML data sources, with no custom development or maintenance required.
Rapid Time-to-Value
Keio University can research and discover insights faster after quickly installing their CData Driver for XML.

Keio University, among the world’s most prestigious universities and the oldest private university in Japan, is notable for its research across humanities and sciences, with over 30 research centers across more than 10 campuses.

Recently, the university’s Global Research Institute conducted the "2040 Independent Self-Respect Project," carrying out interdisciplinary research and development to solve various social issues envisioned for 2040. This data-driven initiative aims to collect information from many sources in multiple formats to analyze and drive the future of industries such as healthcare.

Masako Toritani, a specially appointed professor at the Keio University Global Research Institute, faced the challenge of XML incompatibility with his team’s data visualization tool of choice: Tableau. The CData Driver for XML allowed Toritani to acquire healthcare-related XML data in fewer development hours, letting his team refocus from data management to their society-shaping research.

The Challenge: Access to Vital Research Data

The Keio University Global Research Institute 2040 Independent Self-Respect Project aims to solve various social issues that will arise in 2040, such as a sharp decrease in the working population, an increase in the number of care recipients, and an increase in social security costs. The "Healthy Life Expectancy Extension Project,” part of the larger study, utilizes this research to envision healthcare services that might extend the population’s healthy life expectancy.

In order to analyze social issues related to health and data related to healthcare, Toritani and his team must import data on personal health status and body movements acquired by administrative data, devices, and cameras into Tableau for analysis and visualization. However, some of the data was in XML format and required data conversion to be read by Tableau.

“I thought that if XML data could be read by Tableau like other data, the analysis work could proceed efficiently,” said Toritani.

The Solution: Data Analysis Made Simple

In his search for an effective, easy way to import XML data into Tableau, Toritani found the CData Driver for XML. He downloaded the trial and immediately got started. Within minutes, his team at Keio University was analyzing life expectancy trends within their Tableau instance.

“I decided to buy the CData connector because it was so easy to capture the XML data,” said Toritani. “CData read the XML format file as it was, so I was able to use it as table data in Tableau. We also had a connector for Mac so we could get started right away.”

"I decided to buy the the CData connector because it was so easy to capture the XML data.”

– Masako Toritani, Professor at Keio University

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