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What is a Data Mesh (and why should marketers care)?

You might have noticed that the term Data Lake has recently been replaced by Data Mesh in conversations about modern data stacks. But what does it mean and why is it important for marketers to know...

You might have noticed that the term Data Lake has recently been replaced by Data Mesh in conversations about modern data stacks. But what does it mean and why is it important for marketers to know about it?

Originally coined by Zhamak Dehghani, Director of Emerging Technologies at Thoughtworks, the term has grown in popularity over the past 2 years since its inception, to the point where it’s considered the modern way of making data accessible within organizations across all industries. Here we define the term Data Mesh and explain why marketers should care about it.


What is a Data Mesh?

A Data Mesh is a methodology to design your data architecture in a modular manner that mirrors the microservice architecture popular in Engineering. It aims to provide a common set of tools that allow the provisioning, access control, data catalog, and metrics layer across an organization to be leveraged by different stakeholders.

Imagine your finance and marketing department using the same infrastructure for their data capabilities. Both need different levels of access, and different views on the data, but at the same time, need the same concept of reporting on marketing spend that sums up to one number.


What does this mean?

In essence, think of a Data Mesh as moving from a centralized Data Warehouse or Lake to data as lego pieces that each stakeholder and/or department can combine as they see fit to enable their particular use cases.

End-users don’t care how they get the data, but about what they are trying to achieve with their data. This should be made as easy and as safe as possible, to empower organizations to be data-informed, without the need for each department to create their data silo, or for your data lake to turn into a toxic data dump.

A Data Mesh enables us to share the definition of metrics we care about and not have to redo the data cleaning step for each department. At the same time, it acknowledges that each department would naturally have datasets and metrics, others don’t care about.


Why Does This Matter to Marketers?

If you have a working data pipeline, be it using modern data reporting tools or an E2E solution, there’s no need to panic. A Data Mesh is not necessarily one tool to rule all your data, but more a way of how we think about empowering the users of the data. Small and medium enterprises will often not be at a point when they necessarily benefit from a Data Mesh.

However, if your organization has extensive data needs across the board and some of the challenges you’re having could be solved via the approach described in this blog post, maybe it’s time to consider organizing your data stack more within the Data Mesh philosophy.

 

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