Federated data management is an emerging approach employed by enterprises to improve business outcomes. Read on to learn how it works, and why it works best on a data mesh.
Table of Contents
What is Federated Data Management?
Federated Data Management Benefits
Federated Data Management Challenges
Federated Data Management is Best on Data Mesh
What is Federated Data Management?
Today, data fuels business. But it also creates significant challenges for organizations that aim to be data-driven.
Managing an ever-increasing volume of data is a major undertaking. On top of that, enterprise data is strewn – and often siloed – across numerous on-premise and cloud systems, formats, and technologies. As a result, valuable data is often hard to get at, and always difficult to manage.
Federated data management has emerged as an effective solution for managing raw data and empowering data consumers to put valuable data to use.
Unlike centralized data management, which integrates different databases into one centralized repository (like a data lake or DWH), federated data management leaves an organization’s data where it is. Federated management eliminates the need to implement additional data stores, or ETL/ELT functionality, saving businesses time and money.
A federated data management solution is a single source of data, allowing data consumers to retrieve information from multiple, disparate systems with a single query, in real time. The result is better business outcomes.
Federated Data Management Benefits
Federated data management addresses many of the challenges related to managing an ever-increasing volume of data across disparate systems, technologies, and formats:
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Cost savings
Federated data management does not require a full copy of source data, so businesses do not need to invest in data storage hardware or technologies. Instead, the primary cost is the implementation of the Data Product Platform, which is far more flexible and cost-effective than building a new data store. -
Fast, simple implementation
Because there are no hardware requirements for a federated data management system, implementation is quick and easy. And, since only minimal coding is required, there’s no need for specialized IT staff. -
Enterprise-wide scalability
Federated data management allows for scalability across a company’s entire data landscape, for more effective data governance. -
Faster access to data
When data is treated as a product, federated management enables a single, unified, point of access to all of your company’s data. This offers a faster and more accurate view of the data by eliminating the need to query individual databases. It also makes it easier to share trusted data across the enterprise. -
Minimal risk
Because federated data management does not replicate, or physically move, any data, there’s no risk of any data getting lost. -
Support for ML and AI
Federated data management cleanses data automatically, ensuring data accuracy and consistency, and offers more reliable predictions for Machine Learning and Artificial Intelligence processes.
Federated Data Management Challenges
However, federated data management also has its challenges:
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Technical expertise in individual domains
A basic requirement of federated data management is someone on the domain end with some level of IT knowhow, who acts as the go-to person for issues involving data management and provisioning. This mindset is an evolving process, which data-driven enterprises are just beginning to implement. -
Domain independence vs global governance
Although the shift to domain independence is well underway, without centralized data controls in place, there would be chaos. A focal data team (Center of Excellence), responsible for the coordination and standardization of processes and tools across the business domains, is a must-have. -
Cross-company access to data products
Federated data management calls for the sharing of data products across the organization. When a data product is well built and maintained, it becomes the single source of truth for a particular business entity (e.g., Customer 360), which can be leveraged for operational and analytical workloads.
Federated Data Management is Best on Data Mesh
The key to reaping the benefits of a decentralized, federated approach to data management is with a data product approach, based on data mesh.
Unlike data lakes, data mesh provides each business domain the ability to define, access, and control their own data products.
A data product delivers a trusted dataset for a specific purpose by bundling the data together with its metadata and logic.
A data product platform deployed as a data mesh architecture supports both operational and analytical workloads, and can reside on premises, in the cloud, or across hybrid environments.
In a federated data mesh architecture, businesses gain the advantages of:
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Decentralized data operations
In contrast to data fabric, data mesh allows each business domain to create, consume, and share data products. When business domains control their own data products, they can enhance IT-business collaboration while accelerating time to value. -
Greater speed and agility
Data mesh enables authorized data consumers to define, access, and share data products, quickly and easily. They no longer have to rely on centralized data teams to shield them from the data complexities found in the underlying systems. Instead, a data product approach enables self-service to non-data specialists, throughout the organization. -
Simplified governance and compliance
Data mesh makes it easy to control data quality, privacy and access, at any level of federation. While business domains have the autonomy to create and deliver data products, they must adhere to centralized data governance standards that determine how data will be categorized, managed, discovered, and accessed.
For data-driven enterprises wishing to improve their business outcomes, federated data management – run on a data mesh architecture – is a must.
