by Spencer Nguyen • November 15, 2022
A relatively new term in the world of data management, data mesh refers to the process of creating a single, unified view of all enterprise data. This process can happen in several ways, giving business users easy access to the data they require for decision-making. Several principles guide data mesh design and implementation. This article will discuss the principles of data mesh and how they can help your business get the most out of its data.
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Data mesh architecture enables organizations to build a decentralized data infrastructure. It provides a way to distribute data across multiple nodes or “data meshes” to increase flexibility, scalability, and security. Additionally, data mesh can help reduce the risk of data silos or data lakes by providing a more unified view of an organization’s data.
There are many benefits to using a data mesh, including:
Data mesh is built on four fundamental principles.
A domain-oriented data mesh comprises many small, independent data services that own and manage a slice of the total data. These services are deployed across a decentralized architecture, often following a microservices pattern.
The key benefits of business domain-driven design are:
The key benefits of a decentralized data architecture are:
Data is treated as a product in a data mesh, meaning that data is produced, consumed, and managed as a first-class entity in the organization. To deliver an efficient workflow to end users, data product owners must design, build, and operate data pipeline products that are easy to use and tailored to the actual needs of data consumers.
The products must be:
The benefits of data product thinking are:
A data mesh enables teams to self-serve their data infrastructure needs, while groups can provision and manage their data services without depending on centralized IT operations. Some concerns that IT traditionally addresses, such as data security and compliance, can be delegated to the teams that own the datasets.
The benefits of self-serve data infrastructure are:
Governance in a data mesh is federated, meaning it is distributed among the various teams that own data. This distribution leads to better decision-making about how data should be used and managed since the groups closest to the data are making decisions about it. In the past, centralized IT operations teams often made decisions about data, leading to slow decision-making and immutable data infrastructure.
The benefits of federated computational data governance are:
Data mesh is not without its challenges. Here are some of the challenges you may encounter during data mesh implementation and how to overcome them:
A few key indicators and metrics can help you evaluate the success of data mesh:
DreamFactory is a low-code management platform that can be used to build and deploy APIs. APIs help reduce the complexity of the principles of data mesh and make it easier to implement by providing a more straightforward interface to data. By using DreamFactory, team members can quickly search and access a data platform without worrying about the data mesh’s underlying details.
Your organization can then connect to various data sources, building out a data mesh without having to manage each individual connection. This connectivity saves time and effort when setting up a data mesh.
DreamFactory also offers support when managing your data mesh through role-based access control and auditing features. Using these features, you can track users to ensure that only authorized users have access. Additionally, auditing helps you identify potential problems with your data mesh and fix them before they cause any issues.
If you’re looking for an easy way to get started with data mesh, sign up for a free 14-day trial with DreamFactory and learn more about how we can help your organization succeed with data mesh architecture.
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