Visual data transformation and wrangling tools for column-level operations.
## Overview The Data Transform page provides a visual, code-optional interface for wrangling and reshaping table data through column-level operations. Analysts and data engineers use this page to apply transformations such as type casting, renaming, filtering, and sorting without writing SQL by hand. All transformations configured on this page are compiled into a CREATE TABLE AS SELECT (CTAS) statement that can be reviewed, edited, and executed. This approach keeps the transformation reproducible and auditable while lowering the barrier to entry for users who prefer a point-and-click workflow. ## Key Features - **Visual column transformations.** Select columns from the source table and apply transformations through a guided UI. Supported operations include string manipulation, numeric rounding, date extraction, and conditional expressions. - **Type casting and renaming.** Change column data types (e.g., STRING to INT, TIMESTAMP to DATE) and rename columns in a single step. The UI validates type compatibility and warns on lossy casts. - **Filter and sort operations.** Add WHERE-clause filters and ORDER BY clauses visually. Each filter row maps to a predicate, and the combined SQL is previewed in real time. - **CTAS statement generation.** After configuring all desired transformations, generate a complete CREATE TABLE AS SELECT statement. Copy the statement to the Query Explorer for execution or save it as part of a pipeline script. ## Workflow 1. Open the Data Transform page and select a source table from the catalog browser. 2. Review the column list and apply desired transformations (rename, cast, derive new columns). 3. Add filter predicates and sort orders as needed. 4. Preview the generated CTAS statement in the SQL panel. 5. Execute the statement directly or copy it to the Query Explorer for further refinement. 6. Verify the resulting table appears in the catalog with the expected schema.