Operational Analytics

Plant data answered without making a copy of it.

Operational reporting is the least glamorous workload and the one that decides whether a platform is trusted: the number served and the number reported have to be the same number.

One number: what the application serves and what the report says.

The workload

Reporting that reads the operational source instead of a copy of it.

Aggregates run over the live tables, with document fields filterable beside them. Because there is no extract, a report describes the state of the system at the moment it ran, and the operational view agrees.

Data foundation · 3 data shapes · 4 stages of the operation.

One number: what the application serves and what the report says.

Environment

The system of record

The application writes rows and documents all day, every day.

SQL · JSON / documents

What one layer changes

Two estates, drawn.

The same shapes, held two ways. The difference is not the storage, it is where the agreement between them lives.

Separate systems Copies kept in step
a copy, and a job to keep it honest
Reporting reads a warehouse fed by a nightly job. Disagreements between the report and the application become a standing argument with no owner.
One layer One plan · one contract
one layer · one plan read from one place, as one answer
The report reads the operational layer directly, so there is one source and no reconciliation meeting.
Data shapes

What this workload moves.

Every shape below is a surface of the layer, not a format to be converted into one. They are read and written together.

  • SQL Records, keys and joins
  • JSON / documents Documents and nested objects
  • Time series Measurements and events in time order
Architecture

How the workload reaches the data.

The models this workload names, the path a request takes through them, and the surfaces that speak to the layer.

Operational Analytics · architecture
Workload

The shape of the work itself.

  • Operate
  • Aggregate
  • Segment
  • Publish
Data models

The models this workload names.

  • SQL
  • JSON / documents
  • Time series
The layer

One path from a request to the data it names.

  • Planning Predicates narrow the work before it runs
  • Execution Rows, fields and windows answered together
  • Transactions Readers and writers do not block each other
Surfaces

How the workload reaches the layer.

  • SQL surface The query language the layer is documented in
  • Applications Services and jobs reading and writing as they run
  • Analytics & AI clients The same layer, the same access path
Workload map

The work, stage by stage.

Choose a stage to read what happens there, or a shape to see every stage that handles it. Nothing on the map is a private interface.

PLOMID · Operational Analytics operate · aggregate · segment · publish Select a stage
Stage

Operate

The application writes records and documents

SQL · JSON / documents

Workload map Operational Analytics workload map. Each stage names the part of the operation it carries and the shapes present at that point.
01

Operate

The application writes records and documents

  • SQL
  • JSON / documents
02

Aggregate

Reporting aggregates over the same tables

  • SQL
03

Segment

Document fields used as filters, not decoration

  • JSON / documents
04

Publish

The same numbers serve every consumer

  • SQL
Outcomes

What changes when the data is in one place.

Stated as properties of the system rather than as results we cannot measure for you.

One number

Served and reported values come from one source, so disagreements become bugs.

No nightly dependency

Reporting availability stops being tied to a batch window.

Fields that filter

Document fields are part of the query surface rather than opaque payload.

Fewer copies

Each copy removed is both a cost and a place where the truth could diverge.

Related industries

Where this shows up.

Derived from the industry pages that reference this solution, so the two directions of the relationship always agree.

All industries