Traditional migration
People at the center
Specialist teams drive the work, often sequentially, with people responsible for understanding workbooks, data sources, dependencies and business logic across the migration.
Platform focus
Tableau environments can accumulate years of workbooks, dashboards, published data sources, extracts, calculations and dependencies. Moving them has meant discovery, analysis, rebuilding and validation. A new generation of migration approaches is beginning to change how that work gets done.
A Tableau environment is built around more than dashboards. Workbooks contain views, dashboards, stories and data connections. Published data sources can be shared across workbooks, while extracts can be embedded in workbooks or data sources.
That makes the migration problem less about moving pieces of content and more about understanding how everything fits together. What depends on what? Which definitions need to be preserved? Which content is still in use? And which parts of the estate no longer need to make the journey?
Before anything can be migrated, the estate has to be understood. That means looking beyond what users see to workbooks, data sources, extracts, calculations and dependencies underneath the reporting layer.
A Tableau environment can contain workbooks connected to shared data sources, while calculations, sets, groups, bins, parameters and field customizations can form part of data source metadata. Over time, those relationships can become difficult to see from the reporting layer alone.
The challenge is therefore not to inventory the estate, but to understand it well enough to decide what should move, what should be rebuilt, and what should be left behind.
The objective remains the same: understand the Tableau estate, determine what needs to move, rebuild it on the target platform, and validate the result. What has changed is how the work can be performed.
Specialist teams drive the work, often sequentially, with people responsible for understanding workbooks, data sources, dependencies and business logic across the migration.
Repeatable parts of the migration can be automated, reducing manual effort while people continue to orchestrate the overall process.
AI agents can take on specialized migration workloads and work across multiple stages, while human experts provide oversight, judgment and exception handling.
The shift is not simply from less automation to more automation. It is from people coordinating each stage of migration to specialized agents handling defined workloads in parallel.
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