Data Quality Management

  • Business rule validation
  • ETL & data pipeline testing
  • Regression & unit testing
  • Data profiling & anomaly detection
  • Data reconciliation
Telia
"All-in-one data quality solution for our Vertica data warehouse and its source databases."
Starship Technologies
"Trust is hard to earn and easy to lose. LiTech makes it easier to earn and harder to lose."
Omniva
"Convenient and systematic way to set up and manage your data quality queries."
Registrite ja Infosüsteemide Keskus
"An enthusiastic and motivated team to listen to the client's ideas and wishes."
Holm Bank
"Flexible and quick solution to discover and analyze data quality issues. The application is easy to install and use. Professional and friendly client support. Overall a positive experience with the pilot project."
Up to 50% of data practitioner's time is spent on data quality issues

Endorsements

Values

All of your data validations in one place

Hard coding validation queries into data pipelines and storing them in text files or query editors is unsustainable and does not allow collaboration.
  • Centralized application to store data validations for all of your databases.
  • Easy collaboration between role-based users in your data teams.
  • SQL based test cases for clear expectations about the data.

No more time wasted on manual data testing

Creating data validations manually and sampling data are not efficient or reliable methods for testing large datasets.
  • Dynamic rules automatically applied for data objects without having to write any code.
  • Automatically executed validations and alerts.
  • Anomaly detection using machine learning without having any knowledge about the data.

Reduced delays by detecting errors as soon as they appear

Constant change in data requires systematic testing and monitoring to detect errors and ensure data quality.
  • Prevent negative impact and delays by validating data whenever it is expected to change.
  • Automated data quality reporting with detailed information on errors.
  • Scheduled testing to trigger emails or webhooks on assertion failures.

Data quality integrated into your internal processes

Use API to execute data validations and get results in any of your internal systems.
  • Data validation at any crucial step of your data pipeline.
  • Results exported to other internal tools for reporting.
  • Automated incident management.

Features and attributes

Supported data sources

Is your database missing?
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  • Oracle
  • PostgreSQL
  • SQL Server
  • MySQL
  • MariaDB
  • Redshift
  • Vertica
  • Teradata
  • Snowflake
  • BigQuery
  • SAP IQ
  • SAP Hana
  • Exasol
  • Databricks
  • RESTful API
  • CSV files

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