Priya Nanthakumar

Clean your source data and define field ownership before moving anything into Salesforce.

Modular functions make cleaning logic reviewable and reusable across datasets.

Change detection stops silently when history isn't being written.

Synthetic fixtures beat mocks by testing actual transform logic against realistic data.

Build data quality signals into your SQL pipelines using CTEs.

The right outlier detection method depends on your data's shape and what you're willing to miss.

Catching duplicates before aggregation prevents cascading errors across metrics.

Cardinality ratios reveal whether a column behaves like a category, identifier, or unique key.