Data mesh, one more step towards data democratization

[seonajmulislam00]

Data management is a complex issue and while data lakes are an option, when large volumes of data and complex structures are handled and agility and autonomy are needed, the use of a data mesh becomes the best alternative.

In a data mesh, data is organized by a specific business domain (sales, customer service, marketing, etc.). The teams that use the data own and manage it, creating a self-service data platform.

How does the data mesh model work and what are its advantages? We will tell you about it in this article.

Data Mesh: What is it and how does it work?
Data mesh is a data architecture in which records are organized into specific domains and managed by autonomous computers.

In this sense, the term “mesh” refers to the way domains can easily use data products from other domains, while also referring to how data from multiple domains can be combined to obtain a more holistic view.

By decentralizing data ownership, assigning it to different norway phone number lead business domains, and providing them with a self-service data platform and federated IT governance, it enables domains to develop, deploy, and operate data services more autonomously. In this way, data democratization becomes a reality.

It also provides the ability to model your data with your specific needs in mind, providing a consistent and unified data experience.

While both approaches are used to manage data, data lake and data mesh are not identical concepts.

A data lake is a repository that contains all of an organization’s structured and unstructured data and is managed by a data team. For companies with small data needs or data that doesn’t change too much over time, it’s an efficient solution for storing raw data at any scale.

However, when these needs change frequently, or there are multiple business domains, each with their own data use cases, operating with data lakes is not the best option.

On the one hand, the data team might have to deal with infrastructure issues and, when trying to provide insights, have to localize the data in specific domains.

On the other hand, there could be issues in terms of data quality and data governance , making it difficult to generate reliable insights.

Data mesh architecture is thus revealed as the ideal alternative for companies with complex structures, as it democratises information, facilitating access to data for all users of the organisation.

The 4 basic principles of Data Mesh
Data Mesh is based on 4 fundamental principles that provide agility and scalability, without neglecting the quality and integrity of data throughout the organization.

Decentralized, domain-driven data ownership and architecture
This principle establishes that power and ownership of data should be assigned to different domain teams (marketing, operations, sales, customer service, etc.) so that they deploy and manage their own analytical and operational data services.

In this way, each area owns the data from end to end, modeling it based on its specific requirements and ensuring that it can be delivered to teams in other domains to leverage as products.

This brings us to the second guideline that marks this approach: treating data as a product.
Data as a product
It implies that the owners of each domain are responsible for ensuring that the data is of high quality, reliable and up-to-date so that it can be used by other domain teams and consumers.

Self-service data infrastructure as a platform
In line with this principle, enterprises should have an infrastructure engineering team that provides the tools and systems necessary for each domain team to consume data from other domains while autonomously developing, deploying, and managing interoperable data products.

This allows you to move away from niche skills and complex technologies.

Federated governance
This principle dictates that while there must be a centralized data governance authority, governance must also be integrated into the processes of each domain.

Only in this way will each domain be autonomous and able to guarantee compliance with current regulations, ensuring data privacy.

What are the benefits of applying a data mesh?
For organizations that have a high degree of data change, uncertainty in their data needs, or multiple business domains with specific use cases and transformations, using a data mesh provides numerous advantages.