modules
Data Flow
End the meeting where three departments bring three different numbers.
Every company has lived it: finance reports one number, operations another, sales a third — and the meeting decides truth by seniority. Data Flow removes the vote. One shared transaction boundary means the work-order close, the inventory move, and the ledger post commit as one family, so every consumer reads the same facts at the same time.
Why one boundary beats six databases
Disconnected suites reconcile by meeting: finance has one number, operations another, sales a third, and the truth emerges — weeks late — from whoever argues best. A shared boundary removes the argument. The work-order close, the inventory move, the labor punch, and the ledger post commit as one family with one lineage, so every consumer reads the same facts at the same time.
data Viz
data View
section: thesis
Data Flow guarantees
- Single commit family
- Operational fact, financial post, and event emission succeed or fail together
- Causal lineage
- Every downstream state cites the upstream events that produced it
- Replayable projections
- BI and metrics rebuild deterministically from sealed event history
- No silent divergence
- Competing balances cannot exist; ownership boundaries are enforced, not documented
- section
- capabilities
Who answers for Data Flow
Four roles, four anxieties, one boundary answering each.
data Viz
data View
section: personas
Section 1
col Title: CEO
col Cont: One number per question, whoever asks. The end of competing dashboards and the meetings that reconcile them — decisions accelerate when facts agree.
Section 2
col Title: CIO
col Cont: Six databases collapse into one boundary with replayable projections. Integration inventory shrinks from pipelines to subscriptions.
Section 3
col Title: CFO
col Cont: Reports read posted facts instead of staged copies. Restatements recompute from sealed history rather than archaeology expeditions.
Section 4
col Title: Auditor
col Cont: Lineage traces any number to its sources; replay rebuilds any report bit-for-bit. The burden of proof flips from you to the system.
From reconciliation meetings to one truth
subtitle: What each stage feels like after adoption.
layout: alternating
enable Slideshow: false
slideshow Interval: 5000
Commits unify
date: Phase 1
status: in-progress
Operations, finance, and events commit as one family per business moment.
has Learn More: false
Pipelines retire
date: Phase 2
status: upcoming
ETL jobs switch off as consumers read live projections instead.
has Learn More: false
Meetings shorten
date: Phase 3
status: upcoming
Disagreements resolve by tracing lineage instead of debating copies.
has Learn More: false
History becomes replayable
date: Phase 4
status: upcoming
Any past report rebuilds deterministically for audit or dispute.
has Learn More: false
Data Flow in daily operation
Each surface below moves through the same envelopes — emitted once at the source, consumed everywhere with lineage intact.
data Viz
data View
section: applications
Event Emission
State changes emit canonical envelopes with actor, digest, and source references at commit time. No side-channel updates exist to bypass the log.
Lineage Tracing
Downstream states cite upstream events, so any number traces back to the operations that produced it. Impact analysis runs forward just as easily — change a source and see every consumer.
Live Projections
BI metrics, dashboards, and alerts consume validated events directly. Certified projections carry freshness guarantees; stale consumers show their lag instead of pretending currency.
Replay and Recovery
Sealed history rebuilds any projection deterministically for audit, disaster recovery, or dispute resolution. Replays produce bit-identical results from identical inputs.
Data Flow sub-modules
subtitle: Emit once, consume everywhere.
data View: data-flow:sub-modules
Webhook Events
desc: Business moments delivered provably.
link: /sub-modules/webhook-events
Data Flow questions
Section 1
Is there still a data warehouse?
Analytics consumes live operational state with certified projections. No separate batch warehouse must reconcile before reports agree.
Section 2
What happens when two domains disagree?
They cannot diverge silently: shared boundaries and owner gates force one verdict at commit time, with the losing claim recorded rather than lost.
Section 3
Can history be replayed for audit?
Yes. Sealed event history rebuilds any projection deterministically, so an auditor can re-derive a past report bit-for-bit from its inputs.
Section 4
Do we throw away our BI investments?
No. Dashboards and reports repoint at live projections with the same definitions — they just stop waiting for nightly loads and stop disagreeing with each other.
Section 5
What if the shared boundary goes down?
Topology-matched deployment keeps the boundary local to each site with store-and-forward sync. A network partition pauses convergence; it never forks the truth.
data View
section: faqs
content section
value: A change on the shop floor is visible to finance, planning, and sales in the same moment. Every domain shares the same transaction boundary — no ETL pipelines, no stale dashboards, no month-end surprises about what already happened.
Section 9
Shared transaction boundary across finance, operations, and commercial domains
Section 10
Canonical event envelopes with causal lineage into Timeline-X
Section 11
BI consumption on live state without ETL batches or stale dashboards
Section 12
Replayable projections with evidence preserved per transition
Section 13
No dual writes: one commit family per business moment
Section 14
ARGUS-bound actor identity on every state-changing event
Section 15
Certified metric projections for demand, utilization, and margin
Section 16
Cross-domain queries without reconciliation meetings