The connected data operating system
From disconnected data to a decision you can explain, reproduce and prove.
Keep the systems that already run your business. Connect the identity, scope, version, control, execution, outcome and evidence that disappear between them.
- Identity
- Scope
- Version
- Policy
- Execution
- Outcome
- Evidence
Scroll naturally or use the chapter controls.
The operating gap
One business number. Seven tools. No shared truth.
A result can cross a database, file, SQL query, transformation, quality check, dashboard, notebook and ticket before anyone acts. The number survives; its ownership, version and evidence often do not.
Which definition?
A changed query can look like changed business performance.
Which execution?
A retry or partial result can be flattened into one final status.
Which proof?
Logs, approvals and conversations are reconstructed after the fact.
One connected operating line
advanexus connects the data, the work and the proof.
Supported hand-offs keep an explicit owner and reference. The next step consumes a known version or execution instead of an implied copy, while Assurance links the evidence that is actually available.
-
01
Input
Register a project-scoped source or immutable file version.
Source · FileVersion -
02
Explore
Inspect metadata and run bounded, read-only queries.
QueryExecution -
03
Build
Validate content, transform it and publish a managed table version.
TransformationRun · TableVersion -
04
Check
Turn an expectation into a persisted quality result.
QualityRun -
05
Version
Promote a stable data definition without erasing its predecessor.
DatasetVersion -
06
Decide
Bind analysis to the exact version, permissions and filters used.
ReportVersion · AnalyticsRun -
07
Prove
Trace permitted facts, visible gaps and a bounded evidence package.
Finding · Case · EvidencePackage
A concrete file-to-decision example
Five different files. One governed business picture.
Customers arrive as CSV, orders as JSON, order items as XLSX, and the catalogue and regional targets as delimited text. Each input is inspected, versioned and published before SQL joins the five managed tables into a reusable Dataset.
Customers
Identity, region and customer segment.
Orders
Dates, status and customer relationship.
Order items
Product, quantity and recognised value.
Product catalogue
Category and commercial attributes.
Regional targets
The expected result for each region and period.
Change without lost history
Improve the logic. Preserve what the previous decision used.
In the connected demo, Dataset v1 contains 22 actual-driven rows. Dataset v2 contains all 24 region-period combinations, including two periods with targets but no recognised sales. Reports remain pinned to the version they used.
Dataset v1
The original actual-driven definition remains available to its report.
Dataset v2
The target-driven definition exposes two previously invisible periods.
Controlled recovery
A Master job can check quality, back up, delete, wait, restore and verify each outcome.
From operation to understanding
The dashboard is the result. The platform keeps its context.
Teams can explore with read-only SQL, publish versioned datasets, create reports and dashboards, continue in controlled Python, and discuss the exact object or version. Intelligence can explain and prepare registered actions inside the same permission model.
Governed analytics
Report versions pin exact DatasetVersions; runs retain permissions, row-level controls, filters, diagnostics and artifacts.
Controlled Python
ANPy binds a notebook revision, immutable environment, kernel lifecycle and bounded cell output to the project.
Contextual collaboration
Comments, revisions, mentions and follows stay attached to the object or version the team is reviewing.
Permission-aware Intelligence
Models may propose; deterministic services validate; policy and people authorise state-changing actions.
From “why?” to permitted evidence
Click the result. Follow the story back to its source.
Assurance creates a permission-aware operational view from supported canonical records. It does not invent missing history: verified, unverified, pending, legacy and unavailable evidence remain distinct.
- 01Operational result
Outcome
Start from the KPI, incident, execution or user question that matters.
- 02Entity 360 · Evidence Graph · Execution Story
Exact context
Follow the report, dataset, query, transformation, source, actor and permissions that are available.
- 03Finding · Case
Controlled action
Turn a signal into a finding and a scoped investigation case.
- 04EvidencePackage · SHA-256
Portable proof
Authorised packages can contain bounded HTML, PDF, CSV, JSON, NDJSON or ZIP output with manifest and checksum metadata.
See your own question
Different roles. The same connected truth.
Begin with the decision or obligation you own. The platform connects the operational detail each role needs without reducing everyone to the same dashboard.
Executive or risk leader
Can I trust this KPI, and where is the weak link?
Data owner
What changed between v1 and v2, and who accepted it?
Analyst
How do I turn SQL into a reusable, controlled report?
Data engineer
How do I move data and stop a bad load before publication?
Operations team
Why did the execution fail, what was retried and what was restored?
Auditor or investigator
Who did what, on which version, under which permission, with what result?
What makes it different
Keep the systems you trust. Add the control they do not share.
advanexus does not claim to replace warehouses, orchestrators, catalogue, BI tool or notebook. It adds one operating contract across supported boundaries and keeps uncertainty visible.
Version is a business object
A changed definition becomes a reviewable version, not a silent overwrite.
Evidence starts during execution
Outcomes, actors, scopes and diagnostics do not wait for an audit request.
AI cannot create new authority
Intelligence remains inside registered tools, permissions, confirmation and approval.
Gaps stay visible
Partial, unverified and unavailable never become complete by presentation.
A useful first step
Bring one real process. Connect it from input to evidence.
Start with one source, one business result, one control and one proof obligation. Map the current hand-offs, establish measurable acceptance and show the complete path with your own operating reality.
One input
The source or file that begins the critical flow.
One outcome
The report, decision or delivery people rely on.
One control
The quality, permission or approval that must hold.
One proof obligation
The question you must answer quickly and honestly.