See what you actually have
Import a DataStage XML export and explore the jobs it describes. Read stage layouts, follow links, inspect column derivations and see how jobs relate. Use the original design as the starting point for a migration discussion.
An export describes the job design. Runtime schedules, credentials, external scripts and production data still need their own inventory.
Work from logic to code
Choose a job and a destination: Microsoft Fabric, Databricks or Snowflake. Generate a preview, inspect the transformation logic and work through the parts that need engineering attention.
Keep the source alongside the output while reviewing joins, filters, lookups and calculations. Translation gives your team an artifact to inspect and develop; deployment requires configuration and testing in your environment.
Plan around the work that remains
Use the job inventory, dependency views and complexity indicators to choose a representative pilot. Organize migration waves, record review decisions and keep unresolved questions visible.
Connect each review decision to its source version, generated artifacts and supporting evidence so the next engineer can follow the work.
Grant access to approved accounts
Configured customer deployments support Microsoft Entra sign-in for accounts explicitly provisioned and linked by a PipelineX administrator. Microsoft sign-in never creates an account. Administrator, engineer, reviewer and viewer permissions are enforced by the application, and dedicated customer deployments can use customer-specific data directories.
You approve the PipelineX account and its role, then link the verified Microsoft identity. An unlinked identity receives no access, even when its email matches an existing account.
Prepare a reviewed Fabric deployment
Export notebook and pipeline definitions with a deployment script that integrates Microsoft's fabric-cicd, environment settings and an Azure DevOps pipeline template. Review conversion findings alongside the source. A deployment review is tied to the exact package and destination settings, so changed inputs require renewed review.
Configure Fabric access, review connection bindings and prepare environment-specific releases. See Microsoft's fabric-cicd documentation.
Check migration order and change impact
Check recorded prerequisites before scheduling migration waves. See missing or ambiguous dependencies, cycles and upstream jobs planned to finish too late. Trace downstream jobs for renewed review when an upstream source or recorded artifact reference changes.
The suggested order describes recorded dependencies and sequence child availability. Your team confirms external dependencies and runtime scheduling.
Report remediation and recorded progress
Group conversion blockers by finding and affected job, and export the report. Record remediation, review, testing and deployment hours alongside accepted jobs. Throughput uses entered effort and current review evidence, with missing time coverage shown explicitly.
No recorded hours means no throughput rate. Stale acceptance is excluded, and repeat acceptance does not inflate the job count.
Begin with a representative job
Choose a job that contains real business logic and a manageable set of dependencies. Bring its export, a description of the expected result and your intended target. That creates a more useful starting point than an estate-wide conversion percentage.
Connect the project, people and delivery
Define the project outcome, source identity, destination and delivery lead. Group related jobs into migrations, assign responsibilities and plan waves. My work brings assigned actions back to each person, while shared jobs keep one delivery record per destination.
Explore projects and teams, then follow current evidence through migration reporting.
Inspect what the import actually captured
Follow resumable uploads and parsing activity, then review jobs encountered, imported and not imported. Search import errors, source-capture findings and conversion blockers by job, stage and target platform. Download the diagnostic report to support remediation.
See how DataStage XML import diagnostics connect the Catalog to the engineering work.
Take Fabric packages into repository review
Save a prepared Fabric package to a new branch in a configured GitHub or Azure DevOps repository, open a draft review and follow checks for the recorded commit. Keep package checks, runtime validation and migration acceptance connected to the release.
Explore releases and CI/CD, including customer setup and the scope of each check.