advanexus
Discuss a critical flow

Governed analytics delivery

Explain why a result changed.

Different definitions and input versions can turn the same business question into conflicting reports.

Explore controlled analytics
How advanexus helps

Keep the chosen data and report versions connected to the recorded result. Compare changes and investigate differences before using the numbers.

What your team gains

Connect the numbers to the data behind them and investigate what needs attention.

Try it with your own process

Compare the data version, report definition and filters for one result. Measure time to explain the difference. Version history is not automatically a snapshot of source rows.

Governed analytics delivery

Situations your team will recognise.

  1. How advanexus helps

    Keep the chosen data and report versions connected to the recorded result. Compare changes and investigate differences before using the numbers.

  2. What your team gains

    Connect the numbers to the data behind them and investigate what needs attention.

  3. Try it with your own process

    Compare the data version, report definition and filters for one result. Measure time to explain the difference. Version history is not automatically a snapshot of source rows.

Start with one authorised example. Agree on access, checks and who accepts the result. Compare the same scope before and after; benefits are measured, not assumed.

Discuss this process

Continue exploring

Controlled analytics Pin the data contract. Govern the execution. Explain the result.

Controlled Analytics binds a report to exact DatasetVersions, validates Query Context on the server and retains the permission, RLS, filter, binding and artifact context behind a supported result.

 Governed datasets Turn data definitions into versioned assets with explicit lineage.

Dataset separates exploratory SQL from a reusable data contract. Its stable identity, immutable versions and semantic metadata create a controlled foundation for reports without hiding the source lineage.

 advanexus Assurance Investigate a supported outcome through the available evidence behind it.

Assurance is a permission-aware, read-optimised layer for exploring supported operational evidence. It does not replace the canonical source or manufacture history that was never recorded.

In brief

How does this help with my work?

Keep the chosen data and report versions connected to the recorded result. Compare changes and investigate differences before using the numbers.

How can I check the result?

Compare the data version, report definition and filters for one result. Measure time to explain the difference. Version history is not automatically a snapshot of source rows.