A healthcare-analytics company plans to migrate an Oracle data warehouse to Amazon Redshift. The schema has about 600 tables, 80 views and 150 stored procedures written in PL/SQL. Some views and procedures use Oracle-only functions.
The company must know which objects convert automatically, which need manual work, and how much effort the manual work will take, before it commits to a migration plan.
Which step should the team take first?
Choose one answer.
AA. Create an AWS DMS replication task with the full-load option, and run it to see which tables fail to load into Redshift.
BB. Run an AWS Glue crawler on the Oracle database, and review the tables it discovers in the Data Catalog for the conversion plan.
CC. Rewrite all 150 procedures in Python on AWS Lambda first, and then move the data with DMS once the procedures run correctly.
DD. Use AWS DMS Schema Conversion to assess the Oracle schema, convert what it can, and report the objects needing manual work.
Show the answer and explanation
Answer: D
A. Wrong: A DMS replication task moves rows, and it does not convert the schema objects such as procedures and views. The option reveals data load problems but not the conversion effort.
B. Wrong: A crawler reads table metadata into the catalog, but it does not analyze procedures or views for conversion. The option gives an incomplete picture of the work.
C. Wrong: Rewriting every procedure before knowing which ones convert automatically commits the team to the most effort before the assessment. The option skips the step that gives the plan its scope.
Before a heterogeneous migration, the team needs to know which schema objects convert automatically and how much manual work remains. DMS Schema Conversion assesses the Oracle schema against Redshift, converts what it can, and reports the objects that need manual changes. Replication, catalog crawling and early rewrites do not produce that assessment.
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