SageMaker Unified Studio is a front door, not a runtime. It consolidates the interface while leaving your bill, your IAM design and your infrastructure as code exactly where they were, and it quietly hands you a DataZone governance system to operate. Here is what it genuinely replaces, what it doesn't, the failure modes that bite during adoption, and how to decide whether it is worth it for your team.
Enabling S3 Object Lock on a bucket does not protect the objects already in it. This is how to build an audit evidence repository on AWS that survives the question auditors actually ask, covering retention modes you cannot undo, delete markers that hide protected versions, chain of custody, and the storage bill compliance mode makes permanent.
S3 holds the documents, Iceberg holds the rows, and everything works right up until a number disagrees with its source PDF. Combining structured and unstructured data on AWS is an identity problem, not a storage one. Here are the five failure families that cause it, why each stays invisible until it isn't, and the ingestion order that avoids most of them.
SageMaker Lakehouse is built on the Glue Data Catalog and Lake Formation, so a migration barely moves data. It moves enforcement. Here is the failure mode that bites, the cost levers that actually change, and a decision procedure for working out whether the move is worth it at all.
A Macie bucket labeled "Not sensitive" often just means Macie never read it. Extensionless objects, unsupported storage classes, unreachable KMS keys and quota truncation all produce silence that looks identical to a clean result. Here's how to measure coverage, fix the four gaps, tune identifiers, and keep the bill honest.
Adding another account to a bucket policy takes one line and delegates far more than most people realize. A practical look at AWS cross-account data sharing: the delegation model, the KMS gaps, object ownership, references versus copies, and the guardrails that catch the mistake you will eventually make.