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.

Define Objectives

Start with defining your objectives for the PoC to make sure Data Mesh Manager is the right fit for your organization.

Data Architecture Fit
- Do data products and data contracts conceptually fit to our data strategy?
- Can I map our organization structure to Data Mesh Manager to define data product ownership?
Integrations
- How do I integrate Data Mesh Manager with our data platform (Databricks, Snowflake, BigQuery, on-premise, Legacy DWH, Kafka, Microservices, ...)?
- Git: Can we sync data contracts with Git?
- Access Requests: Connectors, ServiceNow, Immuta, ...
- SSO: OpenID Connect, Entra ID, SCIM2
Data Quality Checks
- Data Contract CLI Automation
Governance
- Roles & permissions
- Write a policy for naming conventions
Customizations & Gaps
- Identify specific requirements and required features

Form the PoC Team

The PoC team typically consists of the following key stakeholders:

Stakeholder	Role & Key Responsibilities
PoC lead	You. Typically a data architect, manager, or senior engineer. Drives the evaluation process. Makes a recommendation.
Executive Sponsor	Approves PoC scope, funding, and success metrics. Aligns PoC with business goals, removes blockers, and makes final decision.
Data Platform Lead	Oversees technical setup and integrations. Deploys DMM, integrates with data platform.
Data Product Owner	Selects pilot data products, validates metadata, and creates data contracts.
Data Governance Expert	Defines governance policies and data contract requirements. Ensures compliance and naming conventions.
Vendor (Entropy Data)	Provides product expertise and technical support. Configures platform and troubleshoots issues.

Get Free Evaluation License

You can use the community edition of Data Mesh Manager for free for an unlimited time.

We offer a free evaluation license for the enterprise edition, which includes all features. Reach out to us to get a free evaluation license for your PoC.

Kick off PoC

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.

Kick-off Meeting

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

Typically, we set up a bi-weekly check-in meeting and set up a Slack or MS Teams channel for quick questions and support.

Support

Schedule a Support Meeting: If you have an issue or question, you can always schedule a support meeting with us: Schedule a meeting
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.
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@entropy-data.com.

Set up Data Mesh Manager

Data Mesh Manager is available as a fully managed cloud version or as a self-hosted version. You can use the cloud version for your PoC, or you can self-host it.

If you use the cloud version, you can skip this section. Just sign up with your work email address at https://app.datamesh-manager.com/create-account.

The self-hosted version of Data Mesh Manager comes as a Docker image and requires a Postgres database. We've created 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 details on how to set up Data Mesh Manager in your environment.

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

Onboard Users

The easiest way to get started is to invite your colleagues to Data Mesh Manager via email. Navigate to Organization Settings -> Members -> Add Organization Member and invite your colleagues to join your organization. You can invite multiple users at once by entering their email addresses separated by semicolons.

For a more advanced setup, you can also use Single Sign-On (SSO) and SCIM2 to onboard your whole organization. Have a look at the SSO guide and the SCIM2 guide for more information.

Define Organization Structure

Data Mesh Manager is designed to support your organization structure and data product ownership. Define your organization structure by creating domains, subdomains, and teams.

Ownership and permissions are managed on the team level.

Follow the Domains & Teams guide to set up your organization structure and check out the Roles & Permissions guide to understand how to manage permissions in Data Mesh Manager.

Add Data Products and Data Contracts

You can add data products and data contracts in multiple ways:

Web UI: The easiest way to get started is to use the web UI. Go to the Studio -> Data Products and click on Add Data Product. You can also add data contracts in the same way.
YAML Editor: If you prefer to work with YAML, you can use the YAML editor to create data products and data contracts. Go to the Studio -> Data Products and click on Add Data Product. Then select YAML Editor.
Git Import: Data contracts can be imported from Git repositories. This is useful if you want to manage your data contracts in Git and use them in Data Mesh Manager. See the Git Integration guide for more information.
Excel Import: Support for ODCS Data Contracts using the easy-to-use Excel template.
Import from Data Platform: Import data products and data contracts from your existing assets. See the Documentation.
API: All resources in Data Mesh Manager can be created and managed via the REST API. This is useful if you want to automate the creation of data products and data contracts or integrate Data Mesh Manager with your existing systems. See the API documentation for more information.

We recommend adding several data products and data contracts to get a feel for your data landscape and how Data Mesh Manager can help you to manage your data products and data contracts.

Configure Integrations

Data Mesh Manager, as a metadata management and governance platform, integrates with your data platform to provide a seamless experience for managing high-quality data products and data contracts. Data Mesh Manager comes with a set of built-in integrations, preconfigured connectors, APIs, and an SDK to integrate with your data platform and other systems in your organization.

Find a list of the available integrations below:

SSO - Connect with your identity provider for seamless user authentication
SCIM2 - Automate user provisioning and role mapping from your identity system
Git Integration - Sync data contracts with your version control repositories
Data Platform Connectors - Connect to your cloud platforms and data warehouses
- Databricks - Integrate with Databricks lakehouse platform
- Snowflake - Connect to Snowflake data warehouse
- Google Cloud Platform - Integrate with BigQuery and GCP services
- AWS - Connect to Amazon Web Services data platforms
- Azure - Integrate with Microsoft Azure data services
SDK - Build custom integrations using our software development kit
Data Contract CLI - Automate data contract testing and validation
Notifications - Notify your team about important events and changes
- Slack - Send notifications to Slack channels
- Microsoft Teams - Integrate with Teams for notifications
- Google Chat - Send alerts to Google Chat spaces

In our experience, the limited time during a PoC might not be enough to set up all integrations. We recommend focusing on the core data platform and sketching out an implementation plan for the remaining integrations, if needed.

Our commitment: If an integration to a common data platform or system is missing, we will work with you to add it.

AI (Optional)

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

Search: Discover your data products through natural language with our semantic search
Data Governance AI (Metadata Checks): Enforce compliance to data governance by continuously monitoring your metadata against your policies
Data Governance AI (Access Request Checks): Let our data governance agent check whether the access request is against your policies
Generate Data Quality Checks: 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 connecting 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.

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

Wrap up

At the end of the PoC, check your objectives and evaluate if Data Mesh Manager is the right fit for your organization.

We would love to welcome you as a customer, but we also understand that Data Mesh Manager is not the right fit for every organization.