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Build trust in your data

Make reliable data the norm

Take action based on your data

Set data alerts to know when your data has met certain conditions. For example, be alerted when there’s bad data so you can fix it. Or know when your inventory’s reached a certain level so you can reorder.

Prevent errors by testing your data

Get automatically alerted of data issues before your transform runs by setting up transform tests. Make sure faulty data, like a transform run on out-of-date information, isn’t shared.

Track important outcomes with transform alerts

Use automated alerts to notify users of any specified outcome of a transform. Highlight potential discrepancies, like unusually low or high returned values, or milestones, like revenue goals.

“ETL is handled easily, Snowflake integration is seamless. Notifications on ETL are helpful.”

Data Reliability

Kevin Denny

Software Engineer

Frequently Asked Questions


What is data reliability?

Data reliability means data is complete and accurate. Instead of relying on someone else to point out errors or having decision makers use bad data, you can proactively catch and fix issues early on. Having reliable data is the foundation for confident decision-making and a successful data team.


What does this require of my team?

Setting up alerts and writing transform tests requires little technical expertise. You can do it all with SQL.

Become a data maestro
Spend more time on data analysis and less time wrangling your data
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