GLOBAL
DataGeir HawkEye
From Atgeir Solutions Inc
A native application for data profiling and analysing Snowflake data statistically to ensure data quality.
Data App Overview
HawkEye is a native application for data profiling that can assist in analysing Snowflake data statistically and ensuring data quality. Users can also discover more about data quality by examining data profile changes over time.
Features
- Dataset Profiling: HawkEye will perform data profiling on the source table.
- Column Profiling: HawkEye provides individual column descriptions based on column data types such as numerical, string, and date.
- Cross-column Profiling: HawkEye allows you to analyse the relationships between columns by providing cross-column profiling. This feature offers insights into the connections and dependencies between different columns.
- Data Labeling: HawkEye utilises machine learning techniques to identify different labels or tags within textual columns. It recognises various entities such as persons, organisations, geographical locations, as well as different linguistic tags like ADJ (adjective), CS (conjunction), CC (coordinating conjunction), and so on.
- Anomaly Detection: HawkEye also offers anomaly detection within the data profiler itself.
- Data Quality Tests: HawkEye also provides data quality rules to ensure the completeness, validity, consistency, accuracy, uniqueness, and timeliness of data. These rules help maintain data integrity and improve the overall quality of the data.
Cloud Region Availability
US West (Oregon)
Canada (Central)
US East (N. Virginia)
US East (Ohio)
US Gov East 1 (Fedramp High Plus)
US Gov West 1
US Gov West 1 (Fedramp High Plus)
Asia Pacific (Jakarta)
Asia Pacific (Mumbai)
Asia Pacific (Osaka)
Asia Pacific (Seoul)
Asia Pacific (Singapore)
Asia Pacific (Sydney)
Asia Pacific (Tokyo)
EU (Frankfurt)
EU (Ireland)
EU (London)
EU (Stockholm)
Europe (Paris)
South America (São Paulo)
Access
Free, unlimited access
Business Needs
Data Observability
HawkEye delivers such observability on Snowflake tables.
Users can also discover more about data quality by looking at how data profile statistics has changed over time.