BI Vendor Sisu Announces New Updates

New tools are aimed at quickly identifying the reasons behind changes in data sets

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BI Vendor Sisu Announces New Updates
Data & Analytics

Published: July 22, 2021

Sandra Radlovački

Sandra Radlovački

BI Vendor Sisu revealed its second update since late 2019 featuring new tools aimed at quickly identifying the reasons behind changes in data sets and expanding into new areas of query analysis.

Founded in 2018, Sisu is focused on answering the question “Why?” in analytics. The vendor provides an automated system for monitoring changes in metrics, with $52.5 million in new venture capital funding and $14.2 million in initial funding round.

The new tools mark Sisu’s second platform update since its initial release and include one to quickly diagnose the results of A/B and other group comparison tests and one that does faster text analysis.

Both move Sisu’s capabilities beyond where they were at launch when its analytics platform was able to provide customers with an overall understanding of why key performance indicators (KPIs) were changing but is comparison analysis was limited to time comparisons such as month over month or year over year.

Berit Hoffmann, Vice President of Product at Sisu, said: “We’re really unlocking entirely new kinds of analysis that we couldn’t do before.”

“They both unlock different capabilities laddering up to our focus of answering this question of ‘Why?’ and helping companies get underneath why their metrics are changing in a way that is faster, more comprehensive and more proactive.”

The vendor’s new comparative testing tool uses augmented intelligence and machine learning capabilities to automatically test thousands of hypotheses in order to explain the results of different comparisons.

Customers who want to use text analysis to discover data points within their unstructured data can use Sisu’s new tool to automate the process of finding common terms and categories, as well as other potential correlations. The result, according to Sisu, is a reduction in the time it takes to prepare data for analysis.

 

 

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