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Master Data Management

One trusted record from every version of the truth.

Autonera finds records that describe the same thing across ERP, supplier and commerce sources, decides attribute by attribute what survives, and keeps every merge explainable and reversible.

How it works

Match three source records into one golden record

Change matching rules and the threshold to see how routing changes, set survivorship per attribute or pin a value directly, then approve, keep separate or unmerge. Every step lands in the merge history.

1. Source records and match signalsConfidence 91 / threshold 85: merge under policy
Matching rules
ERP item masterP1

Updated Mar 02

Manufacturer part no.
Title
Material
Thread
Length
Unit weight
Primary image
Supplier feedP2

Updated Apr 18

Manufacturer part no.
Title
Material
Thread
Length
Unit weight
Primary image
Ecommerce catalogP3

Updated Jan 27

Manufacturer part no.
Title
Material
Thread
Length
Unit weight
Primary image

Highlighted values currently survive. Select any value to pin it for that attribute.

2. Golden record and survivorshipAwaiting decision
  • Manufacturer part no.

    HB-38-16-ZP

    from ERP item master

  • Title

    Hex Cap Screw, Grade 5, Zinc Plated, 3/8"-16 x 2"

    from Supplier feed

  • Material

    Carbon steel, Grade 5, zinc plated

    from Supplier feed

  • Thread

    3/8-16 UNC-2A

    from Supplier feed

  • Length

    2 in

    from ERP item master

  • Unit weight

    0.084 lb

    from Supplier feed

  • Primary image

    hb3816_front.jpg

    from Supplier feed

3. Merge history

  1. Candidate group created: 3 records share part-number signals.

The capability

Matching, survivorship and merge, in one governed flow

Match & Merge is the part of master data management that turns overlapping records into a single golden record. Autonera compares records using configurable rules: exact matches on identifiers such as manufacturer part numbers or GTINs, fuzzy matches on descriptive text, and normalization that removes differences in punctuation, casing and units before comparison.

Each candidate group receives a match confidence score. Groups above the threshold your organization sets can merge under policy; groups below it go to a data steward with the evidence that produced the score. Survivorship rules then decide which source contributes each attribute, using source priority, recency, completeness or an explicit steward choice.

Merges never discard history. Autonera keeps source cross-references, records which rule selected each surviving value, and supports unmerge when a decision proves wrong, so downstream systems can trust the golden record and auditors can see how it was formed.

Problems it solves

Where this work usually breaks down

01

The same part exists three times

ERP, supplier feeds and the ecommerce catalog each carry their own version of a product, with different part number formats and descriptions. Search, pricing and reporting split across duplicates.

02

Merges that cannot be explained

Spreadsheet de-duplication leaves no record of why a value won. When a weight or material is wrong later, nobody can trace which source it came from.

03

Fuzzy matching without control

Loose matching merges products that only look similar, such as Grade 5 and Grade 8 bolts. Without thresholds and review, a bad merge propagates to every channel.

04

Irreversible consolidation

Once records are collapsed, restoring the originals is manual work. Teams become reluctant to clean data at all.

Functional capabilities

What Match & Merge includes

Exact and fuzzy matching
Combine deterministic matches on identifiers with token, phonetic and similarity matching on names and descriptions, weighted by attribute.
Normalization before comparison
Standardize case, punctuation, abbreviations and units of measure so that HB-38-16-ZP and HB3816ZP compare as equals.
Match confidence scoring
Every candidate group carries a score and the contributing signals, so reviewers see why records were grouped.
Configurable thresholds and routing
Set the score above which merges proceed under policy and the band that routes to stewardship, by domain or product class.
Attribute-level survivorship
Choose source priority, most recent, most complete or a steward-pinned value for each attribute instead of one rule for the whole record.
Source cross-references
Keep the identifiers of every contributing record so integrations can resolve old keys to the golden record.
Merge history and unmerge
Record every merge decision and restore the original records when a merge needs to be reversed.
Multi-domain coverage
Apply the same discipline to products, suppliers, customers, locations and reference data.

In industrial operations

Consolidating fastener records after an acquisition

An industrial distributor brings an acquired branch network onto its product master. Both businesses stock zinc-plated hex bolts from the same manufacturers, but part numbers, descriptions and units were entered differently.

  1. Autonera normalizes part numbers and thread notation from both ERP item masters and the shared supplier feeds.
  2. Exact part-number matches above the agreed threshold are grouped and merged under policy, with cross-references to both legacy item numbers.
  3. Pairs that match on description but differ in grade or plating are routed to a steward with the conflicting attributes highlighted.
  4. Survivorship takes dimensions from the ERP, weights and images from the manufacturer feed and the most complete material description.

Result: Branches order against one record per part, legacy item numbers still resolve, and every merge can be traced or reversed.

Autonomous operations

How autonomous execution changes match & merge

Specialized agents run matching continuously as new records arrive, propose groups with evidence and apply merges only inside the thresholds and rules your stewards approve.

Agents carry out

  • Score new records against the master as they are ingested
  • Propose survivorship outcomes per attribute
  • Merge high-confidence groups within policy
  • Flag merges whose source data later changes

People decide

  • Set match rules, weights and thresholds
  • Decide borderline and conflicting groups
  • Approve unmerges and rule changes

Evidence recorded

  • Signals and score behind each match
  • Rule or steward that chose each surviving value
  • Full merge and unmerge history with source keys

Buyer FAQs

Questions evaluators ask

What is the difference between matching and merging?

Matching identifies records that probably describe the same entity and scores that likelihood. Merging creates or updates the golden record from those records using survivorship rules. Autonera keeps them as separate, reviewable steps.

Can we control which source wins for each attribute?

Yes. Survivorship is configured per attribute, so dimensions can come from the ERP, marketing copy from the commerce catalog and weights from the manufacturer, with steward overrides where needed.

How are false merges prevented?

Thresholds decide which groups proceed automatically and which go to review. Rules can also block merges when critical attributes such as grade, voltage or material conflict.

Can a merge be reversed?

Yes. Merge history retains the contributing records and cross-references, so an unmerge restores the originals and records who reversed it and why.

Does match and merge work beyond products?

The same matching and survivorship approach applies across master data domains including suppliers, customers, locations and reference data.

Your next step

See Match & Merge on data like yours.

Bring a real file, catalog or record set. We will walk through how Autonera would handle it and where your team keeps the final say.

Book a Demo