Domo users love data. But some of them really love data, including supersized datasets.

The problem is that, due to their sheer size, these datasets can sometimes mean waiting hours for transformation, impacting user experience and the ability to scale your use of data in a way that meets your needs.

At least, that was the problem. With a new Domo feature called Adrenaline DataFlows, Domo power users can now test the limits of what they can do with all their data.

Released in March 2021, Adrenaline DataFlows is a premium feature that lets you quickly transform even the largest datasets to create optimized, summarized datasets for lightning-fast performance on cards and dashboards.

Use Adrenaline DataFlows to transform ten times larger datasets in less than a tenth of the time it would take compared to traditional DataFlows. That means transformation that used to take hours can now take seconds.

How it works

Adrenaline DataFlows works by summarizing and aggregating massive datasets to create smaller outputs. You can then use these smaller datasets to power dashboards and deliver the performance you require, while drill paths to the original, larger datasets ensure nothing gets left behind.

Adrenaline DataFlows are also useful for situations where calculations need to scan the entirety of the datasets to aggregate data-and where Magic ETL, MySQL, or Redshift dataflows just aren't enough.

Indeed, as you start working with datasets with more than 500 million rows, Adrenaline DataFlows shines-especially if those datasets need to be consumed downstream in dashboards or for transformation. This will improve dashboard performance while preventing dataflows from timing out due to large inputs.

One thing to keep in mind though: We don't recommend using Adrenaline DataFlows for row-by-row transformations or cleansing operations on large datasets.

To learn more about Adrenaline DataFlows, or to try it for yourself, click here.

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Disclaimer

Domo Inc. published this content on 20 July 2021 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 20 July 2021 16:37:06 UTC.