1. Upload the XER files
Start with ordered baseline and update snapshots, source hashes, and parser health.
Primavera P6 analytics for IT buyers
Turn Primavera XER into governed schedule analytics in Snowflake.
Keep XER as the scheduler's lingua franca. Start with baseline and update files, complete a scheduler-led review, then give IT governed facts for Snowflake trends, dashboards, and portfolio reporting.
possible now
iAppSys branded
direct URL demo
Why this matters.
Primavera schedule facts, not raw XER bodies.
Possible now
Primavera schedule facts, not raw XER bodies.
demo
Data boundary
Raw XER bodies and source paths stay out of API, MCP, admin, and visual payloads.
safe
Next conversation
Use Snowflake for governed schedule summaries and portfolio trends.
action
2. Check the baseline
Review schedule health, DCMA orientation, calendars, constraints, and path signals.
3. Check schedule and WBS adherence
Measure date, float, logic, and WBS-level movement against the baseline.
4. Check activities
Inspect changed, delayed, added, removed, critical, and near-critical activities.
5. Check tasks and OBS
Review task findings and preserve available OBS-related coverage for governed downstream modeling.
Choose your deployment model.
SuperWave-XER can be discussed as a product inside your data center, inside your cloud account, or as a managed hosted path. The boundary and operating responsibilities stay explicit.
On premise
Install inside your secure data center with your own network, storage, identity, and operations.
DIY
Run from Docker or source code when you want to own deployment and upgrades.
BYOC
Bring your own cloud account and retain control of tenancy, keys, network, and data placement.
FedRAMP environments
Shape a boundary-specific federal deployment with inherited controls reviewed separately from application controls.
Meet your analytics platform where it is.
Primavera P6/XER remains the scheduler input. Publish governed derived facts and evidence references to Snowflake, Databricks, Google BigQuery, Amazon Redshift, or MotherDuck when the selected architecture approves that path.
Snowflake
Warehouse trends, dashboards, and portfolio reporting.
Databricks
Lakehouse notebooks, pipelines, and governed models.
Google BigQuery
Curated schedule facts for SQL analytics and reporting.
Amazon Redshift
Warehouse-ready review summaries and portfolio views.
MotherDuck
Collaborative DuckDB analytics for lightweight sharing.