TTriveniExecutive Cockpit

Ontology & Data Mesh

The logical layer that lets a half-migrated roll-up still answer one question consistently — model once, federate the data, generate insights anyway.

Triveni Engineering & Industries Limited · FY24 (Mar'24, audited anchor)
One of India's largest integrated sugar & ethanol producers
5,500 employees · 13+ plants & units · 15 export markets
💎 Value creation & investor readinessStep 1 of 7 · the data mesh behind the metricsCompany HierarchyAll journeys
🌐 Enterprise 360 modules· on Ontology & MeshBrowse all 31 views ▾
● LiveBuilt forCIO / Digital Officer / Data· integrate logically, not physicallyCFO / FP&A· one number across many ledgersTransformation PMO· insight before full SAP migration

Triveni can't wait for every mill and export desk to migrate to SAP before it gets answers. The fix isn't one warehouse — it's a shared ontology (so everyone means the same thing) over a data mesh (each segment owns its data as a product), with a semantic layer that federates them. Insights generate today; they just carry a confidence flag where a segment isn't on SAP yet.

Data backing: enterprise ontology · knowledge graph · semantic layer · segment registry · site · org
Shared meaning (T-Box)

The enterprise ontology — what the words mean

Ten classes everything maps to. The Site / Mill is the keystone: it's where segment, leader, entity and geography reconcile.

Company
Company1
Triveni Engineering & Industries Ltd (listed parent)
operates ▾ / owns ▾
The 'who' — accountability & ownership
Segment4
Sugar · Alcohol/Ethanol · Power Transmission · Water & Defence
Operating line / Entity10
operating lines, group companies & JVs
Leader (Person)16
org / accountability
operates ▾ (segment → site)
The keystone
Site / Mill15
the reconciliation point
located in / serves / produces ▾
The 'what & where' — production & demand
Geography5
UP heartland + export rollup
Customer / OMC10+
OMCs, sugar trade, gear & water accounts
Order / Contract
ethanol offtake · gear & water orders
Plant asset1,550
crushing · boiler · distillery · gear units
Supplier6
cane · coal · steel · chemicals
Relationships (predicates)
Triveni operates SegmentTriveni owns Operating line / EntityOperating line rolls up to SegmentSegment operates Site / MillLeader accountable for Segment / lineSite / Mill located in GeographySite / Mill serves Customer / OMCCustomer / OMC holds Order / ContractContract runs on Plant assetSite / Mill produces Sugar / Ethanol / GearSupplier supplies Site / Order
Federate, don't centralize

Each segment is a data product on the mesh

71% of revenue is already site-grain actual; the rest is read in place from legacy site/export systems and reconciled — no big-bang migration required.

Sugar
Sugar · segment data product
Actuals
data quality / grain92%
Alcohol / Distillery (Ethanol)
Alcohol / Distillery (Ethanol) · segment data product
Allocated
data quality / grain84%
Power Transmission (Gears)
Power Transmission (Gears) · segment data product
Actuals
data quality / grain92%
Water & Defence
Water & Defence · segment data product
Region-only
data quality / grain57%
Bagasse Co-generation
Sugar · segment data product
Actuals
data quality / grain95%
Triveni Gears — Naini
Power Transmission (Gears) · segment data product
Allocated
data quality / grain75%
Cane Development & Farmer Services
Sugar · segment data product
Allocated
data quality / grain75%
Exports & Institutional
Sugar · segment data product
Region-only
data quality / grain45%
Triveni Turbine
Power Transmission (Gears) · segment data product
Region-only
data quality / grain45%
Potable Alcohol / IMIL
Alcohol / Distillery (Ethanol) · segment data product
Allocated
data quality / grain75%
10 segment data products (above)
Federated semantic layer
entity resolution · canonical metrics · grain tags
Consumers
Story · Briefing · 360s · Simulator
Defined once, computed everywhere

Governed metrics — the logical layer

Every metric has one definition and a grain. The layer federates it across on-SAP and legacy domains, flagging where a value is allocated.

MetricDefinitionGrainHow it federates across segments
RevenueΣ recognized revenuesite · orderactuals where on SAP; allocated from area where not
Adjusted EBITDArevenue − COGS − SG&A (+ add-backs)segment · entityentity P&L normalized to one chart of accounts
Non-sugar (ethanol & eng.) revenueannuity-like contract revenuecontractfrom SAP SD / SCADA across all segments
Non-sugar mixnon-sugar ÷ revenuesegmentfederated — same formula, many sources
DSOAR ÷ revenue × 365entity · sitelegacy/export entities measured at area grain, flagged
Gross margin(revenue − COGS) ÷ revenueorder · segmentmapped via canonical cost categories
Repeat-offtake rateexpansion − attrition on basecustomer / OMCresolved across duplicate customer records
The payoff

How insights generate before integration finishes

1 · Resolve

Entity resolution matches legacy site / segment / group-company codes to one canonical node — so the distillery data lines up with everything else.

2 · Federate

Query reads each segment's data product in place; the semantic layer maps native SAP/SCADA fields to canonical metrics.

3 · Allocate + flag

Where a segment reports at area level, allocation disaggregates to site on learned drivers and marks it an estimate with a confidence band.

4 · Reconcile

Allocated parts must tie back to the source total; anomalies and duplicate customer/OMC records & suppliers across segments are surfaced.

This is not theoretical — it's how this cockpit already works. The Story, Briefing and 360 views read the same governed metrics over on-SAP and legacy segments alike; 71% of the numbers are site-grain actuals and the balance is SAP-allocated and labelled. As each segment migrates to SAP, its data product's grain rises and estimates flip to actuals — the mesh closes itself.