Where EternityArc fits into how you already work
The same five services — MDM, Data Quality, ETL, Orchestrator and BI — solve different problems depending on where duplicate, siloed or untrusted data is costing you time. Here is what that looks like in 12 industries, step by step.
One customer record across every channel
Loyalty, e-commerce, and point-of-sale systems each keep their own version of a customer. The same shopper looks like three different people, which breaks loyalty-tier calculations and duplicates marketing sends.
Model the customer business entity, run a match plan with fuzzy name and exact email rules across POS, e-commerce, and loyalty feeds, and merge on most-trusted survivorship. Stewards resolve borderline matches in View 360, and Insight360 rolls up unified spend and tier status.
One 360° customer view feeding loyalty, marketing, and support — no more duplicate mailers or mismatched tier status.
Walk through it step by step 5 steps
- Each channel's nightly extract lands in staging and every row becomes a record with its own business ID.
- Reject rules drop rows with no usable email, phone or name before they can be matched.
- The match plan pairs records on exact email and fuzzy name plus postcode, and groups them above the threshold.
- Survivorship keeps the loyalty system's tier and the e-commerce address, field by field.
- Borderline pairs queue for a steward in View 360, who merges or keeps them apart.
- Share of customers seen in more than one channel
- Duplicate sends caught before a campaign
- Steward queue size over time
Client records without the manual reconciliation
Onboarding, risk, and compliance teams each maintain a separate client record pulled from core banking, CRM, and a KYC vendor feed. Reconciling them for a regulatory filing takes days of manual cross-checking.
ETL pipelines bring all three sources in, validation rules check the fields a filing requires and reject what fails, and match & merge consolidates them into one client record with attribute-level lineage back to source. Approval workflows put changes to key fields in front of a reviewer first.
An auditable, single client record with traceable lineage — reconciliation that used to take days happens as records land.
Walk through it step by step 5 steps
- A pipeline joins the KYC feed to core banking on account number and stages the result.
- Validation rules check legal name, date of incorporation and registration number are present and well-formed.
- Match & merge consolidates the client, recording which source supplied each field.
- A change to a key field — legal name, tax residency — goes to a reviewer before it reaches the golden record.
- An Orchestrator flow runs the whole chain on schedule and its log becomes part of the audit trail.
- Fields on a filing traceable to a source
- Records held for review, and how long they wait
- Rows rejected per load, by rule
A single vendor master across plants and ERPs
Every plant runs its own ERP with its own vendor codes. The same supplier ends up registered a dozen different ways, so spend analysis and vendor-risk scoring understate real exposure.
An Orchestrator flow runs the extracts from every plant ERP, a shared vendor business entity is modelled once, and matching consolidates duplicate suppliers into governed golden records. A supplier hierarchy groups subsidiaries under their parent, and Insight360 rolls spend up enterprise-wide.
Procurement sees total spend per supplier and per parent company instead of per plant, surfacing consolidation opportunities and concentrated vendor risk.
Walk through it step by step 5 steps
- One flow runs each plant's extract in turn, so a late plant never blocks the others.
- Supplier names, tax IDs and bank details are matched across plants, exact on tax ID and fuzzy on name.
- Each plant's vendor code stays on the golden record as a cross-reference, so nothing downstream breaks.
- A hierarchy places each supplier under its parent company.
- Insight360 rolls spend up the hierarchy for procurement.
- Distinct suppliers before and after matching
- Spend that rolls up to a parent
- Plants still sending unmatched vendors
Provider directory accuracy at scale
Provider network directories sourced from claims, credentialing, and scheduling systems drift out of sync, leading to inaccurate "find a doctor" results and exposure under network-adequacy rules.
Validation and reject rules stop stale or conflicting provider records at staging, before they reach the directory. Pipelines keep the sources flowing in, and survivorship picks the most trusted source per field — credentialing for licences, scheduling for locations.
A provider directory that's validated as data arrives instead of periodically audited, cutting inaccurate listings and the rework they cause.
Walk through it step by step 5 steps
- Pipelines stage provider rows from each system as they change.
- Reject rules stop records with an expired licence or no practice location.
- The trust matrix ranks credentialing highest for licences and scheduling highest for locations.
- A failed validation lowers that value's trust, so it stops winning merges until it's fixed.
- The directory reads the golden record, never a raw source.
- Listings with a validated location
- Rejects per source, by rule
- Time from source change to directory
Policyholder 360 across claims, billing, and underwriting
A policyholder's claims history, billing status, and underwriting profile live in three systems that don't talk to each other, so adjusters and agents piece together context by hand on every call.
Match & merge resolves the same policyholder across claims, billing, and policy systems. View 360 shows adjusters and agents the golden record with every contributing source beside it, and an Orchestrator flow keeps it current as new claims and payments land.
Adjusters get full context on one screen instead of switching between three systems mid-call.
Walk through it step by step 4 steps
- Policyholders are matched on policy number where present, and on name, date of birth and address where not.
- View 360 shows the golden record with each source record beside it.
- A flow reloads claims and payments through the day, so the view stays current.
- Household relationships are kept in a hierarchy, so an agent sees the whole household.
- Calls answered from one screen
- Policyholders linked across all three systems
- Unmerge requests from adjusters
One resident record across every department
Water, permitting, and billing departments each hold a different version of the same resident record, so a single service request touches three inconsistent addresses and contact numbers.
MDM consolidates the resident entity across departmental systems, validation rules check addresses against reference data on intake, and Insight360 dashboards give department heads a shared view of request volume and resolution time.
One address, one contact record, shared across departments — fewer misrouted requests and duplicate outreach.
Walk through it step by step 4 steps
- Addresses are checked against reference data on intake; unknown streets are rejected with a reason.
- Residents are matched across departments on address and name.
- Record-level rules keep each department to the residents it serves.
- A shared dashboard reports request volume and resolution time per department.
- Requests routed to the right address first time
- Addresses rejected on intake, by reason
- Residents shared across departments
A product and material master for regulated supply
The same active ingredient, pack size, or material is coded differently in R&D, manufacturing, and distribution systems, so batch traceability and regulatory submissions depend on spreadsheets that map one code to another.
Model the product business entity with a product hierarchy — family, product, pack — and a reference entity for controlled codes. Business IDs are generated to a single format, and every change to a golden product record goes through an approval workflow.
One governed product code per item across the supply chain, with an approval trail behind every change.
Walk through it step by step 4 steps
- A reference entity holds the controlled code lists every product must use.
- Validation rules reject products whose codes aren't on the list.
- The hierarchy runs family → product → pack.
- Every change to a golden product goes to an approver, and the approval is kept with the record.
- Products with one code across all systems
- Changes approved vs. rejected
- Codes rejected on intake
Accounts and subscribers in one hierarchy
Enterprise customers sign contracts at head office, buy lines through regional subsidiaries, and pay from shared-service centres. Billing, CRM, and provisioning each see a different slice, so account managers can't see what a customer group really spends.
Streaming intake from Kafka loads subscriber changes as they happen, match & merge resolves accounts across billing and CRM, and a customer hierarchy rolls subscribers up to account and group. Insight360 reports revenue at every level.
Account managers see the whole customer group — every subsidiary and line — on one record and one dashboard.
Walk through it step by step 4 steps
- Subscriber changes stream in from Kafka; priority lanes keep account changes ahead of bulk usage.
- Accounts are matched across billing and CRM on registration number and name.
- The hierarchy runs group → account → subscriber.
- Insight360 reports revenue at every level of the hierarchy.
- Revenue that rolls up to a group
- Lag between a provisioning change and the record
- Accounts matched across billing and CRM
One student record from applicant to alumnus
Admissions, the student information system, finance, and alumni relations each create their own person record, so the same individual is contacted as an applicant, a student, and a donor who never studied there.
Match & merge links each person across systems at intake, survivorship keeps the most recently confirmed contact details, and record-level access rules limit each office to the records it is entitled to.
One person record across the whole lifecycle, with each office limited to the records it should see.
Walk through it step by step 4 steps
- People are matched on student ID where present, and on name and date of birth where not.
- Survivorship keeps the most recently confirmed email and address.
- Record-level rules limit each office to the people it is entitled to see.
- A nightly flow runs the loads and matching in order.
- People linked across the lifecycle
- Contacts sent to the wrong role
- Records each office can see
A location master every carrier agrees on
Warehouses, depots and delivery points are keyed differently in the transport system, the warehouse system and each carrier's feed. Shipments are routed to the wrong dock and delivery performance can't be compared across carriers.
A location business entity is matched on address and geocode, ETL pipelines normalise carrier feeds with Lookup and Expression transformations, and Insight360 compares on-time performance per location across carriers.
One identifier per location shared by every carrier and system, and delivery performance you can compare like for like.
Walk through it step by step 4 steps
- A pipeline normalises each carrier's location codes with a Lookup against the warehouse system.
- Locations are matched on address and postcode; each carrier's code is kept as a cross-reference.
- Validation rules reject locations with no dock or opening hours.
- Insight360 compares on-time delivery per location across carriers.
- Locations shared by every carrier
- Shipments to an unrecognised location
- On-time rate per carrier, per location
A guest profile that follows the guest
Reservations, the property system and the loyalty programme each hold their own guest profile. Preferences recorded at one property are lost at the next, and a loyal guest is greeted as a stranger.
Guest records from each property and channel are matched and merged into one profile; survivorship keeps preferences from the most recent stay, and approval workflows protect loyalty status changes.
Every property sees the same guest, with the same preferences and status, from booking to check-out.
Walk through it step by step 4 steps
- Guest records arrive from each property through a scheduled flow.
- Guests are matched on loyalty number, then on email and name.
- Survivorship keeps the most recent preferences and the loyalty system's status.
- A change to loyalty status goes to an approver first.
- Guests recognised across properties
- Status changes approved
- Profiles with preferences carried over
An asset register operations and finance both trust
Field operations, maintenance and the fixed-asset ledger each describe the same transformers, meters and lines differently. Maintenance history can't be tied to book value, and regulatory asset reports are rebuilt by hand.
An asset business entity is modelled with a site → asset → component hierarchy, records from each system are matched on serial number and location, and validation rules reject assets without a commissioning date or site.
One asset register that ties every maintenance event to a ledger entry, ready for regulatory reporting.
Walk through it step by step 4 steps
- Pipelines stage assets from each system with their native IDs.
- Assets are matched exactly on serial number, and fuzzily on site and description.
- Reject rules hold back assets with no site or commissioning date.
- The hierarchy runs site → asset → component, so a report can roll up at any level.
- Assets matched across all three systems
- Assets held back, by rule
- Maintenance events tied to a ledger entry
Different industries, the same three problems
Almost every scenario above comes down to one of these — and each maps to a part of the platform.
The same thing, recorded many ways
Match & merge resolves duplicates into one golden record, and View 360 lets stewards settle the borderline cases.
Nobody can say which value is right
Trust scores and survivorship pick a winner per field, and lineage shows which source it came from.
Reconciliation is a project, not a process
Pipelines and flows keep sources coming in, so matching happens as data lands rather than once a quarter.
A first project that pays for itself
Most teams don't start with every source. A typical first scope looks like this — and each step leaves something usable behind.
Pick one entity
Customer, supplier, product or asset — whichever duplicate is costing the most today.
Connect two sources
Enough to see real duplicates. Reject rules show you what each source is getting wrong.
Tune the match
Start strict, review the borderline pairs in View 360, and loosen the rules as confidence grows.
Publish, then add
Feed the golden record to one consumer, then add the next source without re-integrating the first.
Don't see your scenario?
Tell us what you're trying to consolidate, clean up or connect — we'll tell you which services fit.
