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Data validation as part of a data warehouse migration from Teradata Vantage to Snowflake

Project duration: 7 months

Brief description

During the migration of a cloud-based enterprise data warehouse (EDW) from Teradata Vantage to Snowflake, the correct transfer of existing ELT/ETL processes is verified. Together with the customer, PTA develops a comprehensive test concept and defines suitable metrics to systematically compare the data sets in Teradata Vantage and Snowflake. In addition, PTA provides support in selecting suitable tools and designs a reporting tool that enables the targeted identification and resolution of potential problem areas.

Supplement

Data reconciliation at the table level serves to systematically identify and quantify discrepancies between the two environments. Particular attention must be paid to database-specific characteristics, especially with regard to data types. A particular challenge is that both environments cannot be operated synchronously, which means that deviations are to be expected, especially in transaction tables. Together with the customer, PTA develops a schedule that defines a suitable strategy for the comparison depending on the size and type of tables (master or transaction tables). Since a large number of tables need to be checked, particular importance is also attached to the runtime of the comparisons during planning. Based on the results of the table comparison, PTA designs a Tableau dashboard to identify specific problem areas.

Subject description

Targeted table comparisons provide customers with a reliable basis for assessing the extent to which the target tables of the productive data processing processes (Teradata Vantage) differ from those of the migrated processes (Snowflake). Using appropriate key figures and visualizations, deviations at different aggregation levels – such as the number of differences between the two environments – can be presented transparently. This allows customers to make targeted adjustments or corrections to the migrated ETL/ELT processes and ensure data quality in the long term.

Overview

Project period01.06.2025 - 31.12.2025

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