Three practices to migrate to dbt faster

Data migrations are a common challenge for data teams, with more than 80% failing due to various complexities and missteps. At Coalesce 2024, insights were shared on leveraging AI to enhance migration efficiency and success, drawing from personal experiences, including leading a major migration at Lyft. Emphasizing speed and a "lift-and-shift" approach is crucial to avoid the pitfalls of trying to address all technical debts and inefficiencies during the migration process. This strategy involves quickly transferring the codebase to a new platform to minimize delays and costs associated with running parallel systems, allowing for post-migration improvements in a less pressured setting. By prioritizing the completion of the migration, teams can focus on delivering new value to the business without being hindered by ongoing migration issues.