Data quality
management tool

  • ETL Testing
  • Data Migration Testing
  • Regression Testing
  • Unit Testing
  • Data Profiling

Save time

Creating test cases manually and sampling data row by row are not efficient or reliable methods for testing large datasets. Reduce manual effort and save time by automating data testing.

Detect errors

The use of continuous integration in development and constant change in data requires systematic testing and monitoring to detect errors and ensure data quality.

Avoid delays

Poor data often means business reports are not reliable and additional development is required. We help you to detect errors in data before any significant negative impact or delays are caused.

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Features and attributes

Data source comparison

Compare datasets from different data souces by comparing rows one-to-one using our built-in compare engine. This allows users to check millions of rows to find errors caused by problems in ETL. It is also possible to compare aggregated values from both sides to check for inequality.

Automated test creation

Automatically generate test cases using reusable dynamic rules. Generated tests are automatically changed in the background to be in accordance with datasource metadata. This means adding or removing columns from a view or table keeps the test case up to date and checks for errors in new columns. LiTech test generation engine allows users to generate tests in bulk to save time and reduce manual effort.

Supported data sources

We support a wide variety of commonly used database engines. Our tool uses JDBC to connect to data sources such as:
  • Oracle
  • PostgreSQL
  • Microsoft SQL Server
  • MySQL
  • Redshift
  • Vertica
  • Teradata
  • SAP IQ
  • SAP Hana
  • MariaDB
  • Databricks
  • Cassandra

Test scheduling

Use scheduler to automatically execute test suites and send alerts when error threshold is exceeded. Tests can be scheduled to execute daily/weekly/monthly or on selected days/custom time.

Automatic alerts

LiTech testing tool sends automatic alerts by e-mail or to Slack channel if error threshold is exceeded on test suite execution. Sending alerts works with our test suite scheduler and REST API to notify responsible users as soon as data errors have occurred.

REST API

REST API endpoints can be used to execute test suites and get test results. This allows easy integration with ETL tools to automate data testing in data pipeline.

Data profiling

Detect sudden changes, deviations and variations in data by systematically profiling objects and analysing profiled data. Use machine learning to predict changes in values, detect possible errors and find anomalies.

Anomaly detection

Automatically analyse test execution results to learn how your aggregated data changes over time. Find errors in dataset by predicting next execution result and comparing it with actual result within error threshold.

Browser based solution

Our platform is accessible via browser so there is no need for any kind of software installation for users. This allows easy-access from different machines within the enterprise network.

Role based users

Our testing tool uses built-in user management system which also integrates with LDAP/Active Directory. Users can manage their own private test cases or share tests with other team members. Roles can be created and assigned to users to only allow test executions for specific databases.

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