What is Data Mesh? | Architecture, Principles, and Benefits
What is Data Mesh?
Data mesh is a decentralized data architecture that groups data according to a particular business domain, such as sales, finance, marketing, and more. The idea behind the data mesh architecture is that data should be managed independently by specific business domains and not in one centralized data platform, thereby making the data more accessible to business users such as data producers and data consumers.
The data mesh approach connects the data producers directly to the business users and data consumers while eliminating the need for a separate data team to process and manage the data.
Principles of Data Mesh
Data mesh can be defined with the following four basic principles:
The domain ownership notion in data mesh states that domain teams are responsible for their data. The three types of domains are aggregated, source-oriented, and consumption-oriented. This idea decentralizes the ownership of operational and analytical data to certain business domains, whether they are the data’s principal users or its sources. In other words, this idea logically separates the operational and analytical data according to the business domain it stands for.
Data as a Product
The data as a product principle applies the notation of product thinking to analytical data. According to this concept, data has users such as data analysts, data scientists, and other user personas outside the domain boundaries. The domain team is accountable for supplying the domain-oriented data as a product directly to the data users in different domains.
Self-serve Data Infrastructure
The self-serve data infrastructure platform’s underlying principle is to adapt the platform in consideration of data infrastructure, provided with all the essential tools, servers, networks, systems, etc., for the users and developers. Hence, the users can begin working on developing data products independently without depending on a central data platform team. Self-service data infrastructure streamlines the data producers to build, deploy, and maintain data products.
Federated Computational Governance
When implementing self-service data architecture, governance must be given more weight. Duplication of data across data domains could result from poor governance. The federated computational governance assigns each domain the task of modeling and evaluating the data’s quality, guaranteeing that the data is safe, legal, and useful. Using the standard as code, the policies as code, and automated testing, federated governance is created and automated monitoring is integrated into each data product. Global regulations and overarching issues are developed by the global data platform and applied to data goods and their interfaces.
Benefits of Data Mesh
Larger firms might benefit from investing in a data mesh. Let’s examine some of the main advantages of data mesh:
- Data mesh reduces the time to insights by using a distributed design that treats data as a product owned independently by each business unit.
- Data mesh enables independent teamwork for each data domain by decentralizing the data operations. Thereby improving scalability and reducing operational costs.
- Data mesh ensures high-quality data deliverables due to self-service data infrastructure and independent governance.
- The distributed architecture in data mesh delivers the data products at high speed without interruptions.
- The use of distributed architecture in data mesh is highly scalable, whereas centralized data architecture cannot scale to the growing volume of data.
- The underlying principle of federated governance in data mesh ensures data security, thereby eliminating the risk of data breaches.
Start Your Journey!
Do you wish to implement data mesh architecture for your business? Reach us today!!! The key to a successful implementation of data mesh architecture is to partner with a company like iLink Digital that has good experience working with a wide variety of clients across different industries.
Our experts will understand the project’s requirements and propose an effective data mesh strategy for your business.