We've Partnered with Braze to Help Power Customer Engagement
Customer engagement is a top priority for many of our own customers, so we’re excited to announce our partnership with Braze. Braze is a...
top of page
🎉 Mozart Data raises $15M Series A to decrease time and resources spent on data infrastructure. Read the news.
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 Make sure faulty data, like a transform run on out-of-date information, isn’t shared.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.
Frequently Asked Questions
01
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.
02
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
bottom of page