What do we mean when we say “this” and how is “that” important? Check out our Qualytics Glossary for terms we use to assist in creating Confidence in your data.

Define Qualytics


Anomaly: Something that deviates from the standard, normal, or expected. This can be in the form of a single data point, record, or a batch of data

Accuracy: The data represents the real-world values they are expected to model.


Burndown Charts: A graphical representation of completed and remaining work versus time.


Comparison: An evaluation to determine if the structure and content of the source and target data stores match

Comparison Runs: An action to perform a comparison

Completeness: Required fields are fully populated.

Conformity: Alignment of the content to the required standards, schemas, and formats.

Connectors: Components that can be easily connected to and used to integrate with other applications and databases. Common uses include sending and receiving data.

  • We can connect to anything within the Spark and Kafka ecosystems, and we have major integrations with leading ELT/ETL providers. If you have a data store we don’t yet support, talk to us!
  • We currently support: Files on Object Storage (CSV, JSON, XLSX, Parquet); ETL/ELT Providers (Fivetran, Stitch, Airbyte, Matillion – and any of their connectors!); Data Warehouses (BigQuery, Snowflake, Redshift); Data Pipelining (Airflow, DBT, Prefect), Databases (MySQL, Po stgreSQL, MSSQL, SQLite, etc.) and any other JDBC source

Consistency: The value is the same across all datastores within the organization.