Startup LiTech helps the university uncover data discrepancies

The University of Tartu has implemented the data management platform provided by the startup LiTech to bring clarity and detect inconsistencies in the university’s databases. 

LiTech, an Estonian startup company that raised its first funding last spring, has strongly contributed to product development. Previously focused primarily on data quality management, LiTech has expanded its service portfolio to include general data management solutions. This includes data catalogue and business glossary solutions, and the recently started cooperation with the University of Tartu.

“We are pleased to announce that the University of Tartu, one of Europe’s most prestigious universities, has started cooperating with us. Partnering with educational institutions marks a significant step for us and underscores the fact that data management issues are not exclusive to large corporations or financial institutions. Data-driven decision-making and value creation through data are becoming standard practices across all organisations,” said Raiko Limmart, the co-founder and CEO of LiTech.

The data management platform developed by LiTech helps identify discrepancies or anomalies in data, which, if left undetected, can pose challenges later. LiTech’s solution checks data compliance with rules, profiles them, analyses the results, and notifies users of any detected errors.

“Currently, the platform has two user groups at the university: the Information Technology Office and the Office of Academic Affairs. Already during the initial testing phase, the software detected data errors in the university’s databases,” said Sten Aus, Head of the Information System Service at the University of Tartu. He added that LiTech’s software is deployed on university servers, and all data processing is controlled by the University of Tartu.

The application has been in development since 2019 to provide a simple solution for detecting and monitoring data errors, improving data quality, and enhancing collaboration between units. In addition, the application helps save time for data engineers and analysts, as it allows automating much of the data testing work. 

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