a large energy provider
From scattered docs to a searchable catalogue
Documentation lived in wikis, spreadsheets and people's heads. We brought it into one catalogue with clear ownership.
Teams now find trusted datasets in minutes, not days.
Catalogue & Metadata
Your Data Catalogue Should Be the Place People Trust. Not Another Tool They Ignore.
A data catalogue is a business initiative, not an IT project. Most organizations already have the tools, the data and the ambition. What is missing is the operating model that turns metadata into daily value. We help you select, implement and run data catalogues so business and technical teams can find, understand and reuse trusted data at scale.
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- Certified
- OwnerFinance
- DefinitionDefined
- Quality98
- LineageMapped
- Used by42 teams
Catalogue Selection
Choose the platform that fits your operating model, not the loudest vendor pitch.
Metadata Automation
Turn technical, business and governance metadata into a living system.
Adoption & Training
Make the catalogue part of daily work for owners, stewards and consumers.
Operate & Improve
Keep metadata quality, workflows and ownership alive after go-live.
Who we work with
A data catalogue is not successful when it is installed. It is successful when people use it to find, understand, trust and reuse data in their daily work.
Why Now
The Catalogue Exists. The Trust Does Not.
Companies invest in catalogues, but users still cannot find data, metadata is incomplete and ownership is unclear. Here is why that gets expensive, and what changes when it works.
Nobody Finds the Right Data
Teams waste time asking around and rebuilding reports. The catalogue exists, but metadata is incomplete, ownership is unclear, and users go back to old habits.
AI and Analytics Need Trusted Metadata
AI, self-service BI and data products all depend on clear context. Without metadata, ownership and lineage, companies scale confusion faster than insight.
Find, Understand, Reuse
A well-run catalogue cuts search time, lifts adoption and turns data into something people actually use.
BeforeAsk around, rebuild, doubt the result
AfterSearch, understand, reuse with confidence
A Fresh Look at Your Catalogue.
A free hour on your catalogue, with quick wins to take away.
Decisions First
Before the Catalogue Works, These Decisions Need to Be Made.
A data catalogue is not just a tool. It forces decisions about what should be documented, who owns it, how metadata is maintained and how users will adopt it. We help clients make these decisions before implementation becomes messy. Drawn from six years of real governance and management work.
Purpose
What should the catalogue solve first?
If the purpose is unclear, the catalogue becomes a generic repository nobody uses.
For example
- data discovery, governance, AI readiness, KPI transparency, regulatory transparency
Scope
What do we catalogue first?
Trying to catalogue everything at once creates noise. A focused scope creates value.
For example
- domains, reports, dashboards, tables, critical data elements, data products, and the documentation cut (application vs domain vs process)
Ownership
Who is accountable for each asset?
Without ownership, and a clear mandate, metadata quality decays after go-live.
For example
- Data Owner, Data Steward, Technical Owner, Approver, plus a clear governance mandate
Documentation standard
What does “well documented” mean?
Users only trust a catalogue when documentation is consistent.
For example
- description, definition, source, owner, steward, lineage, quality status, access rules
Naming & classification
How should assets be named, tagged and classified?
Findability depends on consistent naming, tagging and classification.
For example
- naming conventions, glossary standards, domain tags, sensitivity labels, lifecycle status
Workflow
How does metadata stay alive?
Metadata will not stay current unless it is built into daily workflows.
For example
- asset onboarding, metadata review, steward validation, owner approval, re-attestation, issue handling
Rollout
Where do we start and how do we scale?
A focused pilot creates proof and momentum before scaling across domains.
For example
- pilot domain, first user group, adoption metrics, training approach, feedback loops, rollout waves, reverse-engineer vs front-to-back
And two calls worth debating openly
Worth debating
Lineage first, or ownership first?
Some teams document data lineage first, others nail down ownership before anything else. Both work, but the order shapes the whole rollout, so we decide it on purpose rather than by accident.
Worth debating
How much QA does metadata need?
Light documentation is fast but fragile. Lasting trust in the catalogue only comes from real quality assurance on the metadata, so we agree up front how much rigor is worth it.
What We Deliver
The Full Journey, Not Just the Install.
A catalogue succeeds as an operating model, not a tool. We cover every step, from picking the platform to keeping metadata trusted long after go-live. Nothing left as an afterthought.
Vendor Selection
Pick the catalogue that fits your governance model and budget, not the loudest pitch.
Metadata Model Definition
A model linking business terms, ownership, lineage and quality that people can maintain.
Implementation & Configuration
Configure the tool around real use cases and connect it to your source systems.
Documentation & Migration
Document key assets to a standard and migrate legacy metadata without the old chaos.
Data Catalogue Training
Role-based catalogue training and onboarding so people actually use the tool.
Pilot Selection & Rollout
Pick the right pilot, prove the value, then scale the rollout across domains.
Operational Support & Workflows
Data workflows, quality routines and a run model that keep it alive after go-live.
Workers Council & Governance
Secure workers council approval and align with governance, with clear safeguards.
How We Deliver
From Discovery to a Catalogue That Runs Itself.
A clear four-phase path, then a flywheel that keeps metadata alive.
- Phase 1 · Discover
Understand the Landscape
Map the data landscape, catalogue maturity, metadata sources and pain points.
- Phase 2 · Design
Define the Model
Define the metadata model, operating model, workflows, roles and rollout approach.
- Phase 3 · Implement
Configure & Migrate
Configure the catalogue, integrate sources, document key assets and migrate content.
- Phase 4 · Adopt & Operate
Train, Pilot, Run
Train users, launch pilots, support operations and improve adoption.
Keep It Alive
Metadata Stays Alive Because the Cycle Does.
Documentation goes stale the moment it becomes a one-off project. The flywheel turns it into a routine that keeps getting better.
Capture metadata
Connect source systems and pull technical metadata into one place.
Enrich with business context
Add definitions, ownership, domains and glossary links people understand.
Activate through workflows
Onboarding, approvals and re-attestation keep documentation current.
Improve through usage feedback
Real searches and questions show what to document and certify next.
The Metadata Flywheel
- CapturePull in technical metadata
- EnrichAdd business context
- ActivateTrigger via workflows
- ImproveLearn from usage
The Standard
What a Fully Governed Asset Means.
Trust is not a feeling, it is a standard. We define what governed means in practice so any user, from any team, can rely on what they find. Not everything needs the same level, critical KPIs and regulatory data are held to the highest.
Governance checklist
- Clear, business-oriented description
- Assigned Data Owner and Data Steward
- Linked glossary terms and KPI definitions
- Correct domain and tags
- Consistent naming conventions applied
- Lineage documented where required
Metadata Standards in Practice
The Naming Logic That Keeps Metadata Usable.
A catalogue is only as findable as its names are consistent. We define clear naming standards so assets read the same way across every team. An illustrative framework, tailored to your context in practice.
| Asset Type | Naming Format | Example | Guidance |
|---|---|---|---|
| Business Domain | {Business Domain} | Finance & Controlling | Use clear business domain names, avoid unclear abbreviations. |
| Data Source | {Application} | ERP System | Use the official application name. |
| Schema | {area}_{env}_{layer}_{source} | sales_prd_curated_crm | Keep lowercase and consistent separators. |
| Table | {subject}_{entity} | customer_master | Use descriptive, business-oriented names. |
| Column | {subject}_{attribute}_{id} | customer_address_id | Avoid special characters and uppercase. |
| Glossary Term | {Glossary Term} | Net Revenue | Use terms understood across teams. |
| Dashboard | {Audience}_{Subject} | Operations_Order_Performance | Align with reporting standards. |
| Policy / Standard | {Area}_{Policy}_{Version} | Metadata_Standard_v1.0 | Include versioning where relevant. |
Before You Select a Catalogue Tool.
Tool selection becomes much easier when the operating model is clear. Before comparing vendors, align on the questions that decide whether the catalogue will actually be used.
- What is the primary use case: discovery, governance, compliance, AI readiness or data product management?
- Who are the first real users: stewards, analysts, business users, domain owners, IT or compliance?
- Which metadata should be automated?
- Which metadata must be maintained manually?
- Which systems and BI tools need to connect?
- Are there works council or employee transparency topics?
- How will adoption be measured?
- Who will operate the catalogue after go-live?
Platforms
Catalogue and Metadata Platforms We Support.
We help clients select, implement and operate leading catalogue platforms, always based on business fit, governance needs and adoption potential.
- dataspot.
- erwin DIS
Stakeholder Value
What It Means for Each Role.
A catalogue pays off differently depending on where you sit. Pick a role to see why it matters and what improves.
CDO / Head of Data
- Why it matters
- Data only pays off as an asset when people can actually find and trust it. A catalogue is how that promise becomes real across the organization.
- What improves
- Higher adoption and faster reuse of trusted data
- Less duplicated work across teams
- A governance story you can show the board
CIO / IT
- Why it matters
- Shadow data and duplicate pipelines quietly cost money and add risk. One place for context makes change safer and support lighter.
- What improves
- One source of context across systems
- Fewer access and where-is-this requests
- Safer change with documented lineage
Data Governance
- Why it matters
- Policies mean nothing if metadata is stale and ownership is unclear. The catalogue turns governance into a living operating model.
- What improves
- Clear ownership and stewardship coverage
- Re-attestation that keeps docs current
- Defensible, audit-ready records
Business Users
- Why it matters
- Analysts lose hours hunting for the right data and second-guessing it. A catalogue lets them search, trust and reuse instead of rebuild.
- What improves
- Search that actually finds the right asset
- Confidence in what they are using
- Less rework, more reuse
Compliance / Works Council
- Why it matters
- Personal and regulated data must be handled correctly and transparently. Clear classification and safeguards make that demonstrable.
- What improves
- Visible classification of sensitive data
- Documented lineage and approved processes
- Transparent safeguards for sign-off
Real Results
What This Looks Like in Practice.
Anonymized examples from work across regulated and asset-heavy industries.
a financial services firm
A metadata model for governance and reuse
We defined a model linking business terms, ownership and lineage, then documented the critical assets against it.
Clear ownership and lineage made audits far less painful.
a large industrial group
A pilot that created real user adoption
Instead of a big-bang rollout, we ran a focused pilot on a high-value domain and built the habit from there.
A shelved tool became part of the daily workflow.
Cross-industry
Vendor selection beyond feature checklists
We structured the selection around governance fit and adoption potential, not demo theatrics.
The right platform chosen for fit, not the loudest pitch.
Engage Us
Ways to Start.
Begin with a free conversation, scope a fixed piece of work, or bring in experts as you need them.
Initial Consultation
Start Here
No Cost
60-minute expert conversation
- Ask us anything
- Initial catalogue situation review
- An honest outside perspective
- No sales pitch, no commitment
Catalogue Kickoff Workshop
Recommended
One Day
One day, on-site or remote
- Your catalogue goals and use cases mapped
- A first metadata model sketch
- A platform shortlist for your setup
- A quick-win rollout plan to act on
Outside-In Analysis
Assessment
An external read of where you stand
- Catalogue & metadata maturity benchmark
- A clear gap analysis
- Prioritized recommendations
- An executive-ready summary
Get in Touch
Let's Make Your Data Catalogue Work in Practice.
Oleksandra KarpekoConsultant