Use cases

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.

Retail & CPG

One customer record across every channel

Challenge

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.

How EternityArc helps

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.

Outcome

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
  1. Each channel's nightly extract lands in staging and every row becomes a record with its own business ID.
  2. Reject rules drop rows with no usable email, phone or name before they can be matched.
  3. The match plan pairs records on exact email and fuzzy name plus postcode, and groups them above the threshold.
  4. Survivorship keeps the loyalty system's tier and the e-commerce address, field by field.
  5. Borderline pairs queue for a steward in View 360, who merges or keeps them apart.
What to measure
  • Share of customers seen in more than one channel
  • Duplicate sends caught before a campaign
  • Steward queue size over time
Talk to us about this
Manufacturing

A single vendor master across plants and ERPs

Challenge

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.

How EternityArc helps

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.

Outcome

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
  1. One flow runs each plant's extract in turn, so a late plant never blocks the others.
  2. Supplier names, tax IDs and bank details are matched across plants, exact on tax ID and fuzzy on name.
  3. Each plant's vendor code stays on the golden record as a cross-reference, so nothing downstream breaks.
  4. A hierarchy places each supplier under its parent company.
  5. Insight360 rolls spend up the hierarchy for procurement.
What to measure
  • Distinct suppliers before and after matching
  • Spend that rolls up to a parent
  • Plants still sending unmatched vendors
Talk to us about this
Insurance

Policyholder 360 across claims, billing, and underwriting

Challenge

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.

How EternityArc helps

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.

Outcome

Adjusters get full context on one screen instead of switching between three systems mid-call.

Walk through it step by step 4 steps
  1. Policyholders are matched on policy number where present, and on name, date of birth and address where not.
  2. View 360 shows the golden record with each source record beside it.
  3. A flow reloads claims and payments through the day, so the view stays current.
  4. Household relationships are kept in a hierarchy, so an agent sees the whole household.
What to measure
  • Calls answered from one screen
  • Policyholders linked across all three systems
  • Unmerge requests from adjusters
Talk to us about this
Public Sector & Utilities

One resident record across every department

Challenge

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.

How EternityArc helps

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.

Outcome

One address, one contact record, shared across departments — fewer misrouted requests and duplicate outreach.

Walk through it step by step 4 steps
  1. Addresses are checked against reference data on intake; unknown streets are rejected with a reason.
  2. Residents are matched across departments on address and name.
  3. Record-level rules keep each department to the residents it serves.
  4. A shared dashboard reports request volume and resolution time per department.
What to measure
  • Requests routed to the right address first time
  • Addresses rejected on intake, by reason
  • Residents shared across departments
Talk to us about this
Telecommunications

Accounts and subscribers in one hierarchy

Challenge

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.

How EternityArc helps

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.

Outcome

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
  1. Subscriber changes stream in from Kafka; priority lanes keep account changes ahead of bulk usage.
  2. Accounts are matched across billing and CRM on registration number and name.
  3. The hierarchy runs group → account → subscriber.
  4. Insight360 reports revenue at every level of the hierarchy.
What to measure
  • Revenue that rolls up to a group
  • Lag between a provisioning change and the record
  • Accounts matched across billing and CRM
Talk to us about this
Logistics & Distribution

A location master every carrier agrees on

Challenge

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.

How EternityArc helps

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.

Outcome

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
  1. A pipeline normalises each carrier's location codes with a Lookup against the warehouse system.
  2. Locations are matched on address and postcode; each carrier's code is kept as a cross-reference.
  3. Validation rules reject locations with no dock or opening hours.
  4. Insight360 compares on-time delivery per location across carriers.
What to measure
  • Locations shared by every carrier
  • Shipments to an unrecognised location
  • On-time rate per carrier, per location
Talk to us about this
Common threads

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.

Starting small

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.

1

Pick one entity

Customer, supplier, product or asset — whichever duplicate is costing the most today.

2

Connect two sources

Enough to see real duplicates. Reject rules show you what each source is getting wrong.

3

Tune the match

Start strict, review the borderline pairs in View 360, and loosen the rules as confidence grows.

4

Publish, then add

Feed the golden record to one consumer, then add the next source without re-integrating the first.

Questions

What teams ask before they start

The practical questions that come up when a use case turns into a project.

Do our sources have to be clean before we start?

No. That is what staging is for: reject rules hold back the rows a source gets wrong, with a reason per row, so you see each source's problems without them reaching a golden record.

Which entity should we master first?

Usually the one whose duplicates cost the most today — the customer behind duplicate mailers, the supplier behind under-reported spend. One entity and two sources is enough to see real matches.

What happens to the IDs our other systems use?

They stay. Each source record's own key is kept as a cross-reference on the golden record, so downstream systems can keep using the IDs they know.

Do we need every service for a use case?

No. Many scenarios start with MDM alone and add Data Quality, ETL or Insight360 later. The services share one data model, so adding one needs no re-integration.

Who decides the borderline matches?

Your stewards. Pairs above the threshold merge automatically; pairs close to it wait in View 360 for someone to merge or keep apart — and a merge can be undone.

Can we restrict who sees which records?

Yes. Roles grant modules and objects, and record-level rules narrow each role to the records it is entitled to — by region, department or any attribute.

Don't see your scenario?

Tell us what you're trying to consolidate, clean up or connect — we'll tell you which services fit.

Questions? Ask Arc