Instantly Convert Teradata to Spark

Many Teradata users today want to move enterprise analytics processing to a new open-stack based, scalable, and resilient platform.

For transforming legacy Teradata ETL workloads to cloud/big data based modern platforms, manual identification and conversion of workloads is complicated, time-consuming, and error-prone.

This is how we make it simple

• ASSESSMENT

• TRANSFORMATION

• VALIDATION

• EXECUTION

• Self-service data-driven assessment
• Recommendations for offloadable entities and target query engine
• Optimization recommendations for Big data platform
• Blueprint for your EDW transformation journey

• UI-driven, one-click transformation – ETL scripts and data
• Notebook-based manual editing of queries
• Data structure optimization
• Performance prediction of transformed queries
• In-built UDF library that fills technology gaps (keywords/functions/data types) in the target

• Verification and certification of migrated schema and data
• Data validation at the minutest level usage of a variety of aggregate functions
• Custom query-based validation
• Syntactical and semantic validation of converted logic and scripts
• Comprehensive reports

• Execution of the transformed scripts on any standard big data environment
• Comprehensive reports
• Output artefacts: SQL, Java, Scala, Shell, Python

Solution Overview