what are the five pillars of migration or modernization from a legacy data warehouse to a modern lakehouse?
1. Architecture/infrastructure: Establish the deployment
 architecture and implement a security and governance
 framework.
 2. Data migration: Map data structures and layout, complete a
 one-time load, and finalize an incremental load approach.
 3.ETL and pipelines: Migrate data transformation and
 pipeline code, orchestration, and jobs in this phase. Speed
 up your migration by using automation tools and comparing
 your results with on-premises data and expected results.
 4. Analytics: Repoint reports and analytics for business
 analytics and business outcomes. Reporting semantic layers
 and online analytics processing (OLAP) cubes should also
 repoint to the lakehouse via Open Database Connectivity
 (ODBC) and Java Database Connectivity (JDBC).
 5. Data science/machine learning (ML): Establish connectivity
 to ML tools and onboard data science teams.