Data Governance Consulting & Data CatalogCollibra, Alation, Qlik Talend or DataHub
With our data governance consulting, you make your data reliably findable, understandable and secure to use. We support IT decision-makers, chief data officers and data & analytics teams in selecting, implementing and using modern data governance and data catalog platforms – from the tool shortlist to productive operation.
selection based on your criteria
partner for data integration
certified information security
of data project experience
Which data catalog is right for you?
Choosing the right data governance platform determines long-term success. That is why our data governance consulting supports you from the longlist to the decision – neutral, technology-agnostic and practical. How governance and the data platform work together is shown in our data warehouse consulting.
Longlist and market overview
First, we select suitable tools for your requirements and your IT landscape.
Shortlist and scoring model
Next, we evaluate them against criteria such as usability, compliance and metadata maturity.
PoC support
Then we validate hands-on with real data and use cases from your organisation.
Decision paper
Finally, your CIO, CDO or procurement team receives a clear decision aid.
Which data catalog tool fits your organisation?
Five platforms, five profiles: the right choice therefore depends on your organisation, regulation and existing toolset.
Collibra
This enterprise solution is particularly suited to corporations with complex organisations, regulatory requirements and global data use. Typical audience: large enterprises.
Alation
Alation is especially strong in collaboration and data discovery, making it ideal for data-driven enterprise teams with many tools and use cases. Typical audience: data-intensive corporations and digital champions.
Qlik Talend Data Catalog
This catalog is seamlessly integrated and therefore ideal for companies that already use Qlik Talend for ETL and data flows – with technical and business metadata. Typical audience: mid-sized companies.
DataHub (open source)
DataHub is a flexible open-source catalog and thus a good fit for teams that want to start pragmatically – with a modern UI, data lineage and many integrations. Typical audience: SMEs and technical data teams.
Typical use cases for data catalogs and data governance
Central reference
Business units, IT and data teams use a shared catalog for data sources, lineage and responsibilities.
Self-service analytics
As a result, users find relevant data faster, understand its origin and use it independently for reports and analyses.
Governance and compliance
For example, requirements such as GDPR, BCBS 239 or ISO 27001 are met through role models, classification and audit trails.
Automated metadata and lineage
In particular, automated capture of technical metadata, for example via Qlik Talend, dbt or Airflow, ensures transparency and scalability.
Tool selection as a kick-off
Many customers therefore start with a longlist analysis, proof of concept and rollout of the right tool – we support you end to end.
Foundation for AI
After all, only well-maintained metadata and clear responsibilities make data reliably usable for AI and agentic AI.
Why choose cimt for data governance consulting?
Tool selection and implementation
From longlist and PoC to rollout support – independent advice on Collibra, Alation, Qlik Talend and DataHub.
Award-winning partner
Qlik Elite Partner, Collibra Partner and Alation Partner – with more than 25 years of data project experience, including the award as Qlik Data Integration Partner of the Year 2024.
ISO 27001 certified
Our processes meet high security standards. This is particularly important for governance projects involving sensitive data.
Enablement and coaching
In addition, we offer workshops on governance strategy, role models and data stewardship – both technical and organisational.
Open source and customisable
We also offer DataHub as an open-source alternative that is customisable, extensible and cost-efficient.
Fast project start
Thanks to proven templates, clear methods and experienced consultants, you can start and scale quickly.
Further resources
In our podcast, Rouven Homann talks to Dr. Carsten Bange (BARC) about data catalogs in practice. Our joint webinar with Alation covers how to measure data maturity. Both are in German. You will also find the TDWI poster on the data catalog market.
TDWI poster: Data Catalog (in German)
The data catalog as a data management task: definition, variants, stakeholders, functions, processes and framework conditions on one poster – with cimt as a partner.
Download PDF »
Frequently asked questions about data governance consulting
What is the difference between data governance and a data catalog?
Data governance defines who is responsible for which data, which rules apply and how quality and compliance are ensured. A data catalog is the tool that makes these rules visible: it shows which data exists, where it comes from, what it means and who is responsible for it.
Collibra, Alation, Qlik Talend or DataHub – which tool is right for us?
That depends mainly on company size, regulation, existing toolset and budget. Collibra plays to its strengths in highly regulated corporations, Alation in collaboration and data discovery, Qlik Talend in an existing Qlik environment and DataHub as an open-source entry point. We assess the options neutrally against your criteria.
How long does it take to introduce a data catalog?
A tool selection with longlist, shortlist and proof of concept typically takes a few weeks. A first productive catalog for selected areas can then usually be achieved within a few months – after that, it grows step by step.
Do we need a governance organisation first or a tool first?
Both belong together, because one does not work without the other. Without roles such as data owner and data steward, a catalog stays empty; without a tool, governance remains a paper concept. That is why we usually start with a compact role model and a pilot area in the chosen tool.
How does a data catalog help with GDPR and other regulations?
First, it documents where personal or sensitive data is stored, how it flows and who accesses it. In addition, classification, lineage and audit trails make it possible to meet requirements such as GDPR, BCBS 239 or ISO 27001 in a traceable way.
Why is data governance important for AI projects?
AI models and agents are, however, only as reliable as the data they access. A well-maintained catalog with clear origin, quality and permissions is therefore the foundation for trustworthy AI. Learn more about our AI consulting.
Strategy call on data governance
Would you like to know which data catalog tool fits your organisation or how to introduce data governance efficiently? Our data governance consulting is vendor-neutral and practical – with an initial assessment of your requirements and ideas on tool selection and data culture. We will get back to you promptly.
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Note: This text was created or revised with the support of AI.