Designing Better Datasets for Diagnostic Analytics:
A Sisu How-to Guide

For years, business intelligence (BI) tools and legacy analytics warehouses trained data teams to aggregate, simplify, and streamline datasets into narrow, normalized schemas to work within the tools’ storage and processing limitations.

But a new class of cloud-native warehouses — like Redshift, Snowflake, BigQuery, and Azure Synapse — have overcome many of these scale and speed challenges, making it easier for companies to store all the rich, wide data they capture. These new warehouses eliminate the need to transform and simplify data before load, meaning it’s time to break some old BI habits.

Download this guide for a detailed exploration of why effective diagnostic analytics processes benefit from more granular data, as well as practical exercises for building more useful datasets to improve your own diagnosis.

Thanks for your interest in building better datasets!

Read our blog for more best practices or request a demo to see how Sisu can help you answer the questions in your data.

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Fast.Once you’ve securely connected Sisu to your cloud data warehouse, we’ll start finding significant facts about your KPIs in seconds.

Comprehensive. Sisu uses all your data, in real time, to test every possible combination of factors to help you explain changes in your business.

Continuous.Your data changes on a daily basis, and Sisu never stops asking why on your behalf, proactively updating your team when new facts emerge.

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