Skip to content
Platform · Catalog

Catalog.understandData Catalog & Metadata Intelligence

The catalog is where you finally see what you have: every system, dataset, and column inventoried, tied to business language, and stamped with a certification that's computed and never hand-set.

The product, at a glance

What Catalog is made of.

6 capabilities, and the part of the mechanism this product carries. Every box opens right here, with its full story one tap deeper.

tap any box, or any circle in the mechanism, and it answers right hereknow what matters
What changes

What changes when this is running.

Not promises of speed, but mechanisms: each of these happens because of how the product works, not because we say so.

01

Definitions stop drifting from reality, because the inventory is rebuilt from your systems on every scan, not maintained by hand.

02

Certification arguments end, because badges are computed from live evidence and fall on their own when evidence goes stale.

03

Regulator conversations start from shared language, because the glossary begins from the regulator's own vocabulary, not a blank page.

who lives hereData officeanswers toBCBS 239
The product

Find. Understand. Trust. Use with confidence.

A unified, intelligent view of every enterprise data asset: technical, business and operational. So people find the right data, understand its context, trust its quality, and use it responsibly.

Trust and Scale

Business outcomes

Faster data discovery

Higher data trust and adoption

Less time lost searching

Better decision making

Reduced data redundancy

Regulatory readiness

Stronger data governance

At a glance

The catalog is the front door to trusted data: everything inventoried, tied to business language, and stamped with a certification computed from evidence rather than set by hand.

Discover

Search across all data assets, with AI-powered semantic search and recommendations.

Understand

See complete context: lineage, quality, ownership, policies and usage.

Trust

View certifications, quality scores, controls and the evidence to assess trust.

Collaborate

Comment, ask questions, request access and share knowledge.

Use

Access data safely through approved pathways, APIs, notebooks and tools.

Trigger events

When an institution reaches for this.

An analyst rebuilding a dataset that already exists, because they could not find itThree tables with the same name and three different meaningsA definition that lives in somebody's head and leaves with themA certified badge nobody can explain the basis ofAn examiner asking for the inventory, and the answer taking a fortnight

What it does

Seven stages from finding assets nobody inventoried to watching how the trusted ones get used.

01 · Discover and ingestAutomatically discover data assets and metadata from all sources.
  • Auto-discovery: databases, files, APIs, cloud
  • Continuous scanning and ingestion
  • Schema and metadata extraction
  • Change data capture

Hover, click or use the arrow keys to walk the lifecycle.

The catalog, measured

What the catalog knows about itself: how much of the estate it holds, how that estate is made up, how trusted it is, and whether the pipes feeding it are healthy.

92

of 100 · Strong

Trust by business process

Hover a dimension to see what it measures, or a cell to read the process behind it.

Catalog health

  • Metadata ingestionHealthy
  • Business contextHealthy
  • Lineage coverageHealthy
  • Quality profilesHealthy
  • Policy coverageHealthy
  • User engagementHealthy

Assets by domain

  • Customer24
  • Finance21
  • Risk16
  • Treasury14
  • Operations11
  • Other14
Strong · 80 to 100Moderate · 50 to 79Weak · 0 to 49

What the estate is made of

Tables 42%Views 18%Files 16%APIs 10%Reports 8%Other 6%

An illustrative view for ABC Bank, the site's standing fictional institution. The shape is real; the numbers in your estate are your own.

One person, finding and using a number

The catalog experience end to end. It is the only thread on the site told from the CONSUMER's side rather than the platform's, because the catalog is the one product whose success is somebody else's afternoon.

01 · SearchSemantic, not keywordAI-assisted

Suggestions, synonyms and relevant assets, so the right words are not a prerequisite.

A chain is a conjunction. Take one link out and see what is left.
  • Platform
  • AI-assisted
  • The person

Six steps, and the fourth is the one that matters: a trust score with its workings visible, so the decision to rely on a number is made on evidence rather than on whoever answered the chat.

Key capabilities

Discovery and inventory

  • Auto-discovery: databases, files, APIs, cloud
  • Continuous scanning and ingestion
  • Schema and metadata extraction
  • Change data capture
  • Asset inventory
  • Data source health

Search and discovery

  • Keyword and semantic search
  • Natural language search
  • Faceted navigation
  • AI recommendations
  • Saved searches and alerts
  • Global search across all assets

Business context

  • Business glossary integration
  • Business term mapping
  • Domain and subject areas
  • Descriptions and synonyms
  • Tags and keywords
  • Custom attributes

Asset 360

  • Technical metadata
  • Business metadata
  • Lineage and impact
  • Data quality scores
  • Usage and popularity
  • Related assets
  • Sample data preview

Trust and quality

  • Certification and endorsement
  • Trust score
  • Data quality summary
  • Freshness and timeliness
  • Control and policy status
  • Evidence and attestations

Collaboration

  • Comments and discussions
  • Q&A and data inquiries
  • Ratings and feedback
  • Watch and follow assets
  • Stewardship workflows
  • Community knowledge

Access and usage

  • Access requests
  • Entitlements and policies
  • Secure data access links
  • API, SQL and file access
  • Usage analytics
  • Downloads and exports

Governance integration

  • Owners and stewards
  • RACI and accountability
  • Policies and classifications
  • Regulatory mapping
  • Workflows and approvals
  • Audit and lineage links

Where the platform proposes

AI-powered, and every one of them a recommendation rather than a decision.

Semantic search that understands the question, not just the keyword
Recommend the asset somebody in your role actually needed
Suggest business terms and synonyms from what the data contains
Detect duplicate and redundant assets
Surface personal and sensitive data on discovery
Explain an asset in plain language from its metadata

Manual and AI-assisted

The same work, split. Everything on the left is something a person does; everything on the right is something the platform proposes, with evidence, for a person to accept. Nothing crosses the line on its own.

Manual

A person does this.

  • Decide what a business term means
  • Certify and endorse an asset
  • Own a domain and answer for it
  • Approve an access request
  • Resolve a disagreement about a definition

AI-assisted

The platform proposes. A person accepts.

  • Discover assets and extract their metadata
  • Classify and tag against the ontology
  • Suggest terms, synonyms and descriptions
  • Recommend assets by role and task
  • Detect duplicates and redundancy
  • Compute the trust score from live evidence

Common use cases

Where institutions start

  • Find trusted data for reporting and analysis
  • Understand data lineage and impact
  • Identify data for regulatory reporting
  • Discover personal and sensitive data
  • Reduce redundant data and its cost
  • Support data onboarding and integration
  • Enable self-service data access
  • Data discovery for AI and ML use cases

What it connects to

Databases

  • Oracle, SQL Server
  • Postgres, DB2

Warehouses and lakes

  • Snowflake, Redshift
  • BigQuery, Synapse
  • S3, ADLS, GCS, HDFS

Movement and analytics

  • Informatica, DataStage
  • Airflow, Spark
  • Tableau, Power BI, Looker

Applications

  • SAP, Salesforce, Workday
  • Teams, Slack, Jira, ServiceNow
  • REST APIs, GraphQL, webhooks

End-to-end workflow

  1. 01Discover
  2. 02Classify
  3. 03Enrich
  4. 04Certify
  5. 05Share
  6. 06Govern
  7. 07Use

What gets measured

Against your own baseline.

Catalog coverage scoreCatalogued assetsAssets with business contextCertified assetsAverage time to find dataUser satisfactionAsset viewsOrphan data sources

Who it is for

Data consumers and analystsData stewardsData ownersData engineersBI and reporting teamsData scientistsRisk and complianceAuditors

Integrations

OntaVera GovernanceOntaVera LineageOntaVera QualityOntaVera PrivacyOntaVera RegulatoryOntaVera Reference DataOntaVera Data ProductsOntaVera Trust IntelligenceOracle, SQL Server, PostgresSnowflake, Redshift, BigQueryInformatica, DataStage, AirflowTableau, Power BI, LookerSAP, Salesforce, WorkdayTeams, Slack, Jira, ServiceNow

Built on the OntaVera platform

Shared by every product in the suite.

Financial ontology and knowledge graph

Metadata fabric and connectors

AI and semantic engine

Data lineage engine

Policy and rules engine

Workflow and approvals

Audit and evidence, immutable

Why OntaVera

  • AI-powered semantic search and recommendations
  • Deep business context, with ontology and glossary integration
  • End-to-end lineage and impact intelligence
  • Trust scoring from quality, controls and certifications
  • Built-in governance, policies and access control
  • Open, extensible and built for enterprise scale

The right data.In the right context.Trusted and ready to use.

Try it yourself

See Catalog do real work.

Walk the governed graph the catalog is built on. Every node you tap shows its meaning, its owner, and the trust computed behind it, right here.

setting the stage…
Inside Catalog6 sub-modules

Connect your systems read-only and OntaVera builds the inventory itself: every system, dataset, and column, with business terms attached where the evidence supports the link. Banks care because attestation starts with a complete inventory, and keeping one current by hand is genuinely difficult work at bank scale. This one is derived directly from your systems and moves with them.

What you get
01

Automated discovery runs across native connectors for the systems a first report needs, with OpenLineage ingest and an SDK for the rest, covering warehouses, lakes, core banking platforms, and marts, with no per-connector fees.

02

OntaVera works with metadata only: it reads structure and profiles in place, retains none of your data, and supports BYOK and air-gapped deployment.

03

The business glossary is wired to physical columns, and each term-to-column link is a claim checked against evidence rather than a free-floating definition.

04

Imported inventories and glossaries land as claims as well, so the catalog work your teams have already done is verified against what the scanners actually find.

05

You get coverage you can defend: a system you have not scanned shows up as a gap, because absence is treated as failure.

06

Every addition, edit, and term approval is sealed on the hash-chained ledger.

How it works
1

Connect

Point read-only connectors at your systems; nothing is copied out.

2

Discover

Scanners walk schemas and profiles and build the asset graph automatically.

3

Attach terms

Glossary terms link to columns as claims that evidence confirms or contests.

4

Stay current

Scheduled rescans pick up drift, and a missed scan surfaces as a gap rather than a silent blank.

Questions buyers ask

Asked about Catalog

5 questions

Most catalogs go stale because keeping them current is manual work, and this one is derived from your systems and moves with them. Nothing here is hand-set: certification is computed from live evidence, term-to-column links are claims checked against the data, and a system you have not scanned shows as a gap instead of a blank. The work your team already did is not lost either, because imported inventories and glossaries land as claims and are verified against what the scanners actually find.

How the inventory is built →

It needs read-only connections, nothing more, and it works with metadata only: structure and profiles are read in place, and none of your data is copied out or retained. Deployment supports BYOK and air-gapped setups, so it runs inside the controls you already have.

See the security model →

Discovery, rescans, and status computation run on their own, so the daily work is review and decision rather than data entry. Stewards approve term links, definitions, and exceptions through the decision door, with maker-checker where you require it, and owners attest on cycle with second-line review. The catalog stays current because rescans are scheduled, not because someone remembers to update it.

For any asset, an evidence pack shows when it was certified, on what evidence, and who attested, with every decision sealed on a hash-chained ledger. Definitions, mappings, and policies are versioned, so you can show which rule was in force on any reporting date. Coverage is reported honestly, so an unscanned system appears as a named gap you can speak to rather than a surprise an examiner finds.

How certification is computed →

Agents propose and humans decide: suggested term links, flagged drift, and glossary updates land as claims with their evidence attached, and nothing moves until a steward accepts them. Agents cannot approve anything and they cannot grant certification, because approvals belong to human stewards and status is computed from evidence alone. When a proposal is wrong, the steward rejects it and nothing in the record changes.

Stronger together

One shared record, so products compound.

Every product you add makes this one smarter, because they read and write the same governed record. Start where it hurts most; nothing you adopt later starts from zero.

Getting started

Start small, and prove it on your own systems.

Most banks start with one priority report and five source systems, live in 90 days, then bring in more of the platform behind exit gates they approve. Catalog is part of that first conversation.

The next step

Start with proof, not a promise.

There are three ways in, and each one earns the next. You approve the exit criteria before we spend any more of your time or budget.

01

A 60-minute working session

Bring one report that is expensive to prove. We walk the mechanism against it. Nothing is required from your side.

02

A two-week guided sandbox

Your team works hands-on against a synthetic sample bank. It requires zero access to your systems and zero procurement.

03

A six-week proof on your systems

We use read-only metadata across five systems and one priority report, scored against criteria both sides sign first. The decision it produces is yours.