Data Quality
When It Matters
No compromises! No more busywork in fixing broken data. Reliable quality data is the foundation for any analytics.
Data Accuracy
Correct. Consistent. Unambiguous. It is time to start trusting your data.
High Fidelity Syncs
Out-of-the-box checks to ensure an accurate copy from data source
As data sources are usually fluid and constantly getting updated, the connectors need to be robust to make a copy of the data without missing or duplicating any data. The connectors have built-in checks to provide you the confidence in the fidelity of the integration.
- Checksum-based checks
- Full count checks after close of books
- Approximate count checks
Customized Checks
Flexible interface to customize the quality checks to suit your analytics needs.
Beyond the copy, the data needs to be verified for correctness, consistency and ensure it is ready for analytics. These checks can be fully customized by you to guarantee good quality data for analytics.
- SQL-based and more sophisticated python-based checks
- Flexible scheduling of checks at every step of the pipeline -- at pre-loading (in staging) and post-loading of data
- Additional customized checks on transformed data
Data Freshness
Current. Why work with stale data? Be the hero with real-time analytics and business insights.
Visibility
Full timestamp visibility for every step of the data pipeline and for every batch of processed data to ensure freshness audits
Close of Books
Our freshness guarantee mechanism ensures that at predefined “close of book” moments, the connectors can process out-of-order events or lag in source systems to ensure that the data set is current and complete
Freshness Checks
Configure freshness checks to be processed before running any analytics
Quality Alerting
Make data quality checks first class citizens of your data pipeline.
- Use data events to trigger your analytics so that your analytics run after the data is loaded
- Add barriers to your analytics so that analysis is done only when data quality checks pass
- Get notified when data quality checks are violated
- Use events, thresholds and alerts as breadcrumbs to help debug and get to the root cause of data quality issues
The Only Cost Effective Option
We use cookies on our website. If you continue to use our website, you are agreeing to our use of cookies in accordance with our Cookie Statement. For information about how to change your cookie settings, please see our Cookie Statement.