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Decentralized data architecture with autonomous and interconnected data domains.
In a data mesh architecture, domains allow you to define clear ownership by assigning domains to specific data owners and organize data by business areas to make it easier to discover and access relevant data assets.
Within domains, define data products that package curated information of multiple data assets, making it easier for users to access relevant data products and becomes a shared resource among teams for better collaboration.
Curate specific segments of your datasets to deliver the most relevant information to your data consumers. This avoids information overload and ensures data products are focused and deliver only the most valuable insights.
Define a single table in multiple ways within different data assets, ensuring each data product aligns to business logic. Assign clear aliases to table names and columns, providing valuable context for use.
Data contracts ensure data quality and trust are at a high-level between producers and data consumers.
Write your own tests with SQL scripts to set up monitoring specific to your needs.
Find where the incident took place and replicate events for faster resolution times.
Enable monitoring across multiple tables within sources by our one-page bulk config.
Choose which fields to monitor with 12 available test types such as null%, regex_match, cardinality etc.
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Thresholds for table tests such as Volume and Freshness are auto-detected by our system once data source is connected.
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Alerts are grouped so we don't spam you 100s of notifications. We also deliver them directly to your email or Slack.
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Always experience missing data? Check for data-diffs between any two datasets such as your staging and production tables.
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