What is Qualytics Protect?
Leveraging ML methods to infer data quality rules from historic data, the Qualytics Data Firewall captures erroneous data in-flight and at-rest in data stores. You can capture anomalies in data pipelines and quarantine records; or identify & alert on anomalies in your historical data.
How does it work?
STEP 1
Connect to a
Data Store
Connect to any database, data warehouse, data lake, pipeline or source system through standard-based methods
STEP 2
Profile
Using proprietary algorithms, the Data Firewall infers rich metadata through its deep profiling operation of the historic data in the data store.
STEP 3
Infer & Author Rules
The Data Firewall uses inductive learning, along with unsupervised learning methods to automatically infer data quality rules. You can also write your own using our rich metadata!
STEP 4
Catch Anomalies
The Data Firewall does what a firewall should – stop bad actors at their tracks by applying the Data Quality rules in a flexible manner. Anomalies in flight can be quarantined or alerted; anomalies at rest can be identified and alerted – ultimately, you Protect your data store.
STEP 5
Optional Enrichment
Data Observability is a start to detecting anomalies. Qualytics lets you take confidence in your data to the next level with Enrichment.
Enrich your target data stores with anomalies and metadata in separate tables, enabling your team to take corrective actions with existing data tools.
STEP 6
Learn, Learn, Learn
Data is always changing and so should rules. The Data Firewall leverages unsupervised learning to detect model and data drift in metadata, while supervised learning ensures rules are always aligned with user needs
How do we qualify your data?
The Qualytics 8
Qualytics uses these 8 fundamental categories to assess data quality.
WE CONNECT TO THAT
Connectors
Qualytics fits seamlessly into your data stack, with effortless integrations from multiple data sources.
