Migrating data from legacy systems to modern data warehouses such as Snowflake, Synapse, BigQuery, Redshift, and Teradata is a complex process that requires careful planning to reduce risk and speed up value delivery. Data modeling is a critical step in this transition, as it helps organizations understand stakeholder requirements, identify and analyze all data sources, and establish clear data lineage. By creating a complete architectural blueprint and documentation, teams gain a clear view of how systems will function. This structured approach supports smoother modernization, improves data quality, and ensures that data warehouse implementations are efficient, scalable, and aligned with business goals.

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