Data Mesh Manager

Start Proof of Concept (PoC)

How to make a successful PoC with Data Mesh Manager

Typical Evaluation Process

From kick-off to decision, the evaluation process typically takes 4-6 weeks.

  • kick-off:
    • kick-off meeting (optional)
    • set up slack or MS Teams channel (optional)
    • biweekly meeting (optional)
  • install and configure Data Mesh Manager
  • onboard users and teams
  • onboard data products and data contracts
  • configure access management
  • set up data governance
  • evaluation with data product teams and data consumers
  • commercials, feedback
  • wrap up and decision

Get Support

You can do the PoC on your own, and that's fine for us.

But you are not alone! We are here to help and want to make your PoC a success.

Schedule a Support Meeting

Sometimes, the best way to get started is to talk to someone. We offer a support meeting for all who are in the process of evaluating Data Mesh Manager.

Schedule a meeting with us.

Customer Portal

If you found bugs, want to request additional features, or track a specific discussion, you can create and track a ticket through our customer portal. Tickets are tracked, and you can see the status of your request.

Community Support

Community support is offered in Slack in the channel #datamesh-manager. We are also available in that slack if you simply want to chat us up.

Email Support

And you can always reach us via support@datamesh-manager.com.

Evaluation License

You can use the community edition of Data Mesh Manager for free, without having to get us involved.

If you want to evaluate enterprise features such as SSO or SCIM, we're happy to provide you with an evaluation license for your PoC. Just contact us through one of the support channels above.

Setup and Installation

If you use the SaaS solution, you can skip this section.

Data Mesh Manager comes as a Docker image and requires a Postgres database. We've already creates templates to install Data Mesh Manager in different cloud environments such as Azure, AWS, Kubernetes, and Docker. Have a look at the git repository for more help.

You might need to configure the Data Mesh Manager to your needs. Have a look at the configuration guide for more information.

Integrate with your data platform

Data Mesh Manager only manages metadata, and never has access to the data itself.

Organization, Users and Teams

Data Products and Data Contracts

  • manage in web ui
  • connect with git (ci/cd, git provider)

Access Management

  • manual
  • connectors
  • 3rd party systems

Assets (Optional)

  • connectors
  • import data contract from asset / assign to data product

Data Contract CLI (Optional)

  • data contract test

AI (Optional)

Data Mesh Manager comes with a bunch of AI-powered features:

  • Discover your data products through natural language with our semantic search
  • Enforce compliance to data governance by continuously monitoring your metadata against your policies
  • Let our data governance agent check whether the access request is against your policies
  • Make your text-based data quality executable by converting them to executable SQL code

For those features to work, you need to connect Data Mesh Manager with an AI-model under "Settings" > "AI". You can use our managed model or bring your own (BYO) LLM. When you use the self-hosted option, we recommend to connect with your own LLM so your data never leaves your environment. We currently support OpenAI on Azure, but are happy to work with you to add your LLM hosting provider of your choice.

Security and Permission Model

Adopt best practices to design data products and data contracts

  • contract-first
  • data-first
  • leverage the data contract cli
  • data contract workshops using excel template
  • integrate with git

Communicate with your stakeholders

Why a data marketplace?

A data marketplace enables business users to easily discover and access high-quality, consumer-ready data products. Unlike traditional catalogs, it prioritizes usability by curating data with clear semantics, quality guarantees, and defined ownership. Data contracts ensure structure, trust, and transparency across domains. This approach reduces noise, boosts data adoption, and streamlines governance. Ultimately, it transforms data sharing into a scalable, self-service experience. Learn more.

Why data contracts?

Data contracts establish a clear, shared understanding between data providers and consumers by defining the structure, semantics, and quality expectations of data exchanges. They serve as a communication tool, often created collaboratively before implementation, ensuring that data products meet agreed-upon standards. By making expectations explicit, data contracts facilitate automation in testing, schema validation, and access control, enhancing trust and reliability in data products. Additionally, they support a self-service model where data consumers can request access, and providers can manage approvals efficiently, aligning with data mesh principles. Learn more

Why open standards?

Open standards, such as the Open Data Contract Standard (ODCS), provide a vendor-neutral framework that ensures consistency and interoperability across data ecosystems. By defining clear structures for data schemas, quality metrics, service-level agreements, and stakeholder roles, ODCS facilitates seamless collaboration between data producers and consumers. This standardization enables automation in validation, monitoring, and governance processes, enhancing trust and reliability in data products. Data Mesh Manager natively support ODCS, allowing organizations to integrate these standards into their workflows effortlessly. Embracing open standards like ODCS empowers organizations to build scalable, transparent, and efficient data ecosystems. Learn more

Pricing and Commercials

Pricing is based on the number of teams you have that own data products. We're happy to give you a custom quote that fits your company.