Data Mesh in Action

Discover the newest paradigm in the data world and see how you can benefit from it.


Data Mesh is a relatively new concept. It's a paradigm shift from centralized and monolithic data architectures to decentralized ones. It addresses the challenges of scaling and managing the ever-expanding universe of data in large organizations.

In a Data Mesh approach data is treated as a product, promoting domain-oriented decentralized data teams to take ownership of their data products. They are responsible for the quality, governance, and delivery of the data product.

An organization adopting Data Mesh uses technological standardization to ensure interoperability, maintain quality standards, and reduce operational complexities.

Data Mesh provides an alternative to the “centralized” organizational and architectural pattern of the data lake with a distributed and decentralized architecture that's designed to help enterprises to:


Data Mesh is a journey that doesn't always start from scratch. Many enterprises already have pieces in place that could contribute to a successful Data Mesh architecture. Before putting the pieces together, you have to know where you're at in your Data Mesh journey. Find out today, with the Data Mesh Readiness Assessment.

Test your Data Mesh Readiness

Enable agility and business scalability

Reduce the time-to-market of business initiatives

Lower Maintenance Costs

Allow a fair and transparent internal cost allocation

Check out how easily Data Mesh can be adopted with Witboost. Click the top right corner of the preview below for a quick tour.

Even in a rapidly evolving scenario, we have already developed a concrete experience with Data Mesh projects. Get to know a few of our projects below, including case studies, white papers, Knowledge Base articles, podcast episodes, and videos.

 Discover Our Data Mesh Stories Below!

Data Mesh Success Cases

Learn more about how these data-driven companies have used Witboost to steer their Data mesh Journey.


Watch the video to learn more about Scania's Data Mesh evolution.


Learn more about Enel Group's Data Mesh architecture.


Learn more about Poste Italiane's Data Mesh Implementation.

White Paper: The Practical Guide to Successful Data Mesh Implementations


This whitepaper explores how businesses can identify, avoid, and solve the most common obstacles for scaling a successful Data Mesh initiative.

It also covers how Witboost helps an organization solve these challenges, maintain a technology-agnostic approach and embrace all the core Data Mesh principles for a functional Data Mesh implementation delivered faster and with lower risk than other approaches.

Starting with the gradual implementation to demonstrate its potential and quick time-to-market and ending with consolidation across many years, organizations can use this 3-phased approach to implementing Data Mesh and assessing its value by themselves.

The whitepaper delves into:

  • The challenges of each obstacle

  • The impacts of each obstacle

  • The solution to each obstacle

Get Your Free Copy


Data Product Flow: The Agile Lab Approach to Data Products

Data Product Flow – How To Discover and Create Your Data Products 

Interviewed by Scott Hirleman, the founder of the Data Mesh Learning Community, Paolo Platter talks about Data Product Flow, the methodology that Agile Lab is currently using to help customers moving their organizations to Data Mesh.



Learn About Our Unique Methodology


How to Identify Data Products? Welcome "Data Product Flow"

Data products are designed to help organizations get more value from their data by looking at it in a new way. Data products can be used to improve decision-making, automate processes, and create new products and services.

But how do you identify data products?

Getting Started with Data Mesh

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Data Mesh A-Z Guide

Still new to Data Mesh?
Read this guide that navigates Data Mesh-related terms from A to Z, providing a focused description of each term to facilitate exploration and learning in a short format.

Download the Free Guide

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Getting Data Mesh Buy-in

Created by the Data Mesh Learning Community (of which our own Antonio Murgia is an author and which we are proud members of), this white paper presents the successes and challenges of Data Mesh buy-in and adoption.

Read this free-to-download resource and get started on your Data Mesh Journey today (no registration necessary).


Our Data Mesh Knowledge Base

Technology Abstraction in the Data Mesh

In this article we address the mistake companies make by staking their Data Mesh on several technologies.

Data Mesh in Organizational Culture

This article introduces the theory of organizational culture and leadership by Edgar Henry Shein as a framework to analyze and address cultural actions.

Scaling Data Mesh in Large Organizations

This contribution wants to shed a light on some of the limits that a Data Mesh implementation will experience sooner or later.

How to Model Data Products

When it comes to modelling Data Products, people panic. There are no clear rules, only some conceptual, and not actionable, indications.

Monoliths Integration

This article focuses on the technical issues of a company that is in the stage of breaking data monoliths to enable inbound and outbound integration with the Data Mesh.

Automate Data Mesh

Dive into our practical approach when it comes to metadata. It's open source and used by many of our clients to enable much-needed automation for their Data Mesh journey.

Data Mesh Discussions

Data Mesh Interview - Big Data LDN 2023

In this interview during Big Data LDN 2023, Paolo Platter, our Co-Founder and CTO discussed Data Mesh with Ravit Jain and Christina Stathopoulos.

Implementing Data Mesh Initiatives

Paolo Platter, CTO at Agile Lab discusses data mesh, from basic principles to use-case specifics, with Christina Stathopoulos, Data Whisperer and Data Expert. Key parts of the discussion:

  • Our role in the Data Mesh Paradigm
  • 4 Pillars of Data Mesh
  • Challenges in implementing Data Mesh for enterprises
  • Data Mesh Benefits (vs. monolithic models)
  • Client Use Case: Our first Data Mesh implementation


Data Mesh Deep-Dive

Our co-founders, Alberto Firpo, CEO, and Paolo Platter, CTO, discuss Data Mesh aspects, such as use cases, organizational changes required to adopt the paradigm, and transitioning from different architectures (such as Data Lake and Data Warehouse) to Data Mesh.

The Data Stack Show

Decoding Data Mesh: Principles, Practices, and Real-World Applications

Paolo Platter, our CTO and Co-Founder was part of an all-star team on Data Mesh comprised of its creator Zhamak Dehghani, Founder and CEO of NextData and Creator of Data Mesh, and Melissa Logan, Director of the Data Mesh Learning Community.

They joined hosts Eric and Kostas to discuss what Data Mesh is, the shift from monolithic to microservices, how to get started with data mesh, define what data products are and what they are not, and much more


Witboost: Data Mesh Enabler

Discover Witboost as an enabler of Data Mesh architectures, thanks to its technology agnostic design and close adherence to the four pillars of the Data Mesh paradigm. Discover how Witboost can help you implement Data Mesh faster, following the paradigm's pillars below:

Domain oriented Ownership

A unified workspace for each domain with full autonomy in delivering value, while leveraging the platform's capabilities end-to-end.

Self-Service data infrastructure as a Platform

Profoundly automate your Mesh with Templates. Each has full provisioning automation along the entire data product lifecycle.

Federated Computational Governance

Enforce your governance with computational policies along the delivery process. All handled by the platform team.

Data as a Product

Standardize Data as a Product thinking with Templates and boost interoperability across data silos, ultimately breaking them down.


Witboost is the ideal platform upon which to build a Data Mesh solution for companies of any size. When Vishnu Chintamaneni, director of Engineering and Anjali Gugle, Product Security and Data Strategy Manager at Cisco (one of the largest technology companies in the world, ranking 74 on the Fortune 100 list) envisioned “Stellaris” - a new data and API platform based on the Data Mesh architecture, the choice was obvious: build it on the Witboost platform.

The project aims at solving the scalability problem of their current architecture, due to highly coupled pipeline decomposition, hyper-specialized ownership, and loss of context. All this leads to ineffective data management and weak governance, stifling productivity and innovation. The solution is a Data Mesh architecture built on Witboost.

This will allow Cisco to become more data-driven, democratize data, making it available securely for proper use, increase data literacy and data quality, enable visibility, clarify ownership, and provide transparency. In other words, the goal is to solve the issues presented by centralized, monolithic data lakes by treating domain-based data as the end-product. This will empower separate business domains to host and serve their datasets in an easily consumable way and also enable analytics that truly reap the benefits of its data.