By Brynne Henn - May 24, 2021
Michael Vizard, writer for Venture Beat, interviewed Sisu CEO and Founder, Peter Bailis, to get the details behind Sisu’s new Smart Waterfall Charts that offer a new approach to telling clear stories from complex data.
As Michael writes,
“The Sisu platform scans schemas, data types, cardinality, and other related attributes of data sets regardless of the physical location. It then automatically transforms the information into a proprietary format that can be queried. The challenge has been that, before now, someone still needed to manually massage the results of those queries to visualize them for users via a dashboard.
The Smart Waterfall Charts tool now automates the visualization of queries launched via its platform, said Sisu CEO Peter Bailis. Previously, analysts would have spent hours creating visualizations of the results of data queries, he noted. ‘It’s the last mile of the process,’ he said.
That approach makes it possible to visualize queries of massive amounts of data, using machine learning algorithms and statistical analysis to surface attributes and relationships, Bailis said.
Sisu is not the first platform to employ scans to analyze data, but Bailis said it is uniquely able to analyze massive amounts of varied types of data at scale because of the way it analyzes data. Rather than requiring all data to be moved into a single data lake or warehouse, Bailis said it’s often more practical to index data wherever it resides rather than going to the trouble and expense of moving it.
Business analysts can also now, for example, not only more easily surface what is occurring, but also discern why it is happening because the platform automatically highlights recent changes to related data sets in real time, Bailis noted. That’s critical because analysts are not always close enough to the business to know which queries should be launched across sets of data that at first glance might not appear to be related.”