A framework for validating data in ETL/ Migration projects involving heterogeneous data stores.
Advaith is a scalable, high-performing and reliable framework.
Supports data validation on any RDBMS as well as Big Data technologies.
Data validation can be performed on data lake stores – currently supports parquet format files and very soon, will support other file formats.
Supports a wide range of transformations in data validation.
The framework can also compare data in RDBMS and data.
Advaith will be made available as a cloud offering.
ADVAITH (Agile Development and Validation In The Hadoop) can be seamlessly integrated into the Data Vision+, the testing tool build by Trianz
This integration enables the Data Vision+ to extend the capabilities to test data on Big Data platforms; compare data on RDBMS with Big Data and vice versa
Scales data validation in a distributed architecture based on data loads and thus, improves the overall efficiency of data validation cycles
Automates regression cycles and reduces the total cost of quality
Highly user friendly and intuitive interface enables quick self-service of the product
A compliance-friendly digital store of all test cases, test executions and cycles with complete audit and control information
Generates reports and dashboards showcasing quality improvements with each cycle
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The team from Trianz went above and beyond to generate additional revenue sources for us, apart from fulfilling our original ask. This is something we’re extremely appreciative of, and we look forward to associating with Trianz repeatedly.
Trianz has not only helped us reap manifold business benefits, but has also bolstered our relationship with our customers. Ongoing support is a bonus!
Our collaboration with Trianz has been exceptional with conspicuous benefits. The platform now effectively manages customer reference data, while addressing data accuracy and quality issues.