Accenture + Collibra: 2023 data mesh reading list

Thought leadership

Created in 2019, the concept of the data mesh is one of the most-discussed topics in data management. As more and more zettabytes of data are created every year, organizations everywhere are seeking better ways to accelerate turning data into better decisions, better products, and ultimately better organizations.

Over the last year, together with Accenture, we’ve created a number of helpful data mesh assets, and we wanted to pull them together to help you quickly get to what you need.

Data mesh 101: What is data mesh? 

Ok you get it. Data mesh is important. But what is it? What does it mean to be a data mesh organization?

Data mesh is a social and technical data management approach that promotes decentralized, domain-driven, data-as-a-product design at scale and offers a path beyond the shortcomings of legacy, centralized architecture.

This approach maximizes the value of data by reducing friction for data creators and consumers by design. By decentralizing domain ownership, data mesh empowers business domains to control their data destiny by creating high-value, trustworthy data products that are easily consumed by the organization.

Flexibility is inherent to data mesh, encouraging an evolutionary approach, but it requires strategic commitment and investment.  

Still interested in learning more? We have some great resources to get you up to speed on what data mesh is and why it’s important to your business:

“For a distributed data platform to be successful, domain data teams must apply product thinking with similar rigor to the datasets that they provide; considering their data assets as their products and the rest of the organization’s data scientists, ML and data engineers as their customers.”

– Zhamak Dehghani

Source: ‘How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh.’ May 2019

Data mesh in practice: Implementing data mesh across your organization 

You now know what data mesh is. You can define the data mesh organization and explain its benefits to your boss. But what is your next step? How do you actually incorporate data mesh into your data management strategy?

The first step is to understand the rich framework of data mesh, which is based on four guiding principles. You can read more about each of these principles in our blogs: 

Principle 1: Domain-driven ownership

Put ownership in the control of the people closest to the work, the domain experts.

Read the blog

Principle 2: Data as a product

A product is something of a value that’s planned in a rigorous process over time. Data products should get the same treatment.

Read the blog 

Listen to the podcast:

Principle 3: Self-service data infrastructure

The data mesh organization abstracts complexity for the domain owners and reduces friction for data consumers. When data products can be seamlessly developed, shared, and consumed, an organization puts itself in a position to truly foster innovation.

Read the blog 

Principle 4: Federated computational governance

The concept of federated data governance enables each domain to maintain control over its own data while still adhering to a common set of standards and practices. FCG drives more efficient, effective data sharing across the organization, as well as greater transparency and accountability in decision-making.

Read the blog 

Data mesh in partnership: Driving adoption with the help of a partner 

You know what data mesh is. You know the four pillars to start your data mesh journey. Now you want to grow, but adoption isn’t always easy. 

You can share your knowledge, strategy, and best practices with the business but how do you really get up and running and drive adoption? 

We know data mesh can be complex — and that’s why we are partnering with Accenture to help you embark on your data mesh journey.

The next step? Reach out to your Collibra representative () and your Accenture representative () to get hands-on assistance. 

Can’t wait to learn more? Check out these additional resources.

 

Related resources

Webpage

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Podcast

The Data Download

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