Navigating the Data Landscape through Decentralisation

By Jonny Dixon, Senior Project Manager at Dremio.

  • 3 months ago Posted in

In the ever-evolving data landscape, the emerging trend of data decentralisation is changing the way businesses work with the information they hold. However, it presents different challenges to traditional and conventional data architectures. These systems, which heavily rely on elaborate data pipelines that connect source systems to data lakes and warehouses, are now perceived as slow and expensive.

To directly address these issues, the decentralisation of data has been gaining visibility. With three distinct trends driving it forward and representing different ways of how we access and leverage data: the data lakehouse, data virtualisation, and data mesh.

Posing the question, is it now expected that all businesses should adopt this unified solution for data management?

A data lake and data warehouse walk into a bar…

The emergence of the data lakehouse signifies a crucial trend in the decentralisation of data. It brings together the concepts of data lakes and data warehouses by using a unified storage system, meaning organisations can keep both raw unstructured data and structured data in one place. Making it far more accessible within the business and fostering collaboration among data engineers, analysts, and data scientists to promote innovation.

It is a type of data architecture that leverages data warehouse commands, often in SQL, to query data lake object stores quickly, whether on-premises or in the cloud. This is crucial for those who want to experience enhanced analytics performance, flexibility, cost effectiveness and improved data quality.

By building analytical systems around data lakes, using open formats that are non-proprietary and widely supported, businesses can create unified datasets, which would be accessible by diverse tools without replication. Helping to break down data silos and allowing teams to access a centralised repository of data, reducing redundancies, and ensuring a single source of truth.

This shift towards unified datasets within a data lakehouse contributes to the broader trend of data decentralisation where this information is more accessible and adaptable across a business.

The Power of Data Virtualisation

Not all data should be in one place. However, retrieving and integrating data that is spread across different storage systems and formats, can be time-consuming.

Data virtualisation allows organisations to access and manipulate data without having to know where it is stored or how it is formatted. It simplifies data management by creating a layer of abstraction, so users can work with a unified and virtual representation of the data. This enhances overall accessibility and decision making by eliminating any delays that arise from needing to locate and format data for analysis, all the while maintaining data integrity and security.

Whilst organisations can swiftly adapt to the ever-changing needs of their data landscape, virtualisation can equally introduce critical challenges in data management. For example, it can be difficult to work to scale with the huge amounts of data. Despite data virtualisation being a key part of data decentralisation, which helps businesses flexibly work at scale, it can still create complexities when dealing with large data sets. Similarly, data virtualisation could leave businesses at the mercy of the underlying system’s performance, in terms of performance bottlenecks, network latency and software limitations.

Overall data virtualisation plays a crucial role in modern data architecture by providing a more efficient and flexible way to manage and utilise data resources across an organisation. This innovative approach streamlines processes through enabling quick access and utilising data sources. Data virtualisation becomes a catalyst for empowering businesses to develop a real time understanding of the data landscape.

Data Mesh Revolution

Similarly, data mesh offers a new way of organising data. Allowing for different groups to handle their own data products, ensuring that the data is relevant, well-organised and delivered quickly, leading to more meaningful and timely insights. Thereby creating a landscape where businesses can derive more meaningful and timely insights. Through embracing a data mesh model businesses can unlock the full potential of their data resources, resulting in informed and strategic decision making.

Data mesh offers true potential for meaningful change, by steering businesses away from traditional centralised data management towards organising and gaining value from their own data resources. This enables faster decision making for the business and better accessibility for employees, whilst also facilitating easier data discovery and even higher quality and security of data. The transition to a decentralised approach, introduces faster and more flexible ways to manage and utilise data across an organisation.


In short data lakehouses simplify storage, bridging the gap between the flexibility of data lakes and the structured nature of data warehouses. Simultaneously, data virtualisation enhances security and accessibility through enabling a unified view of data across an organisation. Lastly, data mesh distributes data among domain specific teams which ensures faster decision making and even better quality.  

These three trends driving this forward significantly shift how we approach data management and transform how a business manages their data. Each approach offers its unique advantages. Businesses may choose more than one of these approaches to harness the power of the solution whilst also aligning with the specific needs of their organisation across their diverse data estate.  

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