Suppose you want to migrate data from Snowflake to Tatiyah, how would you do it?

Migrating data from Snowflake to Tatiyah involves a structured Extract‑Transform‑Load (ETL) process. First, assess the source schema: list tables, columns, data types, and dependencies. Next, design a target schema in Tatiyah that preserves semantics while optimizing for the target platform’s storage model. For extraction, use Snowflake’s COPY INTO command to unload data to an intermediate storage layer such as an S3 bucket or Azure Blob. If the data volume is large, partition the unload by date or key to enable parallelism. During transformation, handle data type conversions (e.g., Snowflake’s VARIANT to Tatiyah’s JSON), cleanse nulls, and apply business rules. Tools like dbt or Fivetran can orchestrate these steps and maintain lineage. Finally, load the transformed data into Tatiyah using bulk insert APIs or native connectors. Validate the migration by comparing row counts, checksums, and sample records. Automate the pipeline with Airflow or Prefect, and monitor for failures. This approach ensures minimal downtime, data integrity, and repeatability.