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.

Financial Services

Client records without the manual reconciliation

Challenge

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.

How EternityArc helps

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.

Outcome

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
  1. A pipeline joins the KYC feed to core banking on account number and stages the result.
  2. Validation rules check legal name, date of incorporation and registration number are present and well-formed.
  3. Match & merge consolidates the client, recording which source supplied each field.
  4. A change to a key field — legal name, tax residency — goes to a reviewer before it reaches the golden record.
  5. An Orchestrator flow runs the whole chain on schedule and its log becomes part of the audit trail.
What to measure
  • Fields on a filing traceable to a source
  • Records held for review, and how long they wait
  • Rows rejected per load, by rule
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Healthcare

Provider directory accuracy at scale

Challenge

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.

How EternityArc helps

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.

Outcome

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
  1. Pipelines stage provider rows from each system as they change.
  2. Reject rules stop records with an expired licence or no practice location.
  3. The trust matrix ranks credentialing highest for licences and scheduling highest for locations.
  4. A failed validation lowers that value's trust, so it stops winning merges until it's fixed.
  5. The directory reads the golden record, never a raw source.
What to measure
  • Listings with a validated location
  • Rejects per source, by rule
  • Time from source change to directory
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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
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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
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Energy

An asset register operations and finance both trust

Challenge

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.

How EternityArc helps

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.

Outcome

One asset register that ties every maintenance event to a ledger entry, ready for regulatory reporting.

Walk through it step by step 4 steps
  1. Pipelines stage assets from each system with their native IDs.
  2. Assets are matched exactly on serial number, and fuzzily on site and description.
  3. Reject rules hold back assets with no site or commissioning date.
  4. The hierarchy runs site → asset → component, so a report can roll up at any level.
What to measure
  • Assets matched across all three systems
  • Assets held back, by rule
  • Maintenance events tied to a ledger entry
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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