Future of financial services lies within the data mesh

The digital revolution has heralded a new age for the financial services industry. What has stood out the most, however, has been the massive accumulation of data – both professional and personal – that digitisation has enabled. This expansion in the volume of available data has been accompanied by an increase in variety. In addition to the variety in the data itself, there is now also a huge variety of data-gathering processes, methodologies, and storage systems, all of which have their own infrastructure and protocols. The load of keeping all these systems operating in sync frequently leads to slowdowns and logjams. In the fast-paced and highly competitive world of financial services – one in which new challengers arise every day – a business that loses ground will not survive for long.

Data mesh, first proposed in 2019 by Zhamak Dehghani of ThoughtWorks, a global tech consultancy firm, provides a solution to this issue. By applying a new approach to the principles of modern software engineering, data mesh offers analytical data management based on a distributed architecture. It enables end-users to access data at its source, without needing to be transported to a traditional centralised architecture like a data lake or data warehouse. 

In a data mesh, each organizational unit within a company —for example, marketing, sales, customer service, and more—has its unique data product owners which own domain-specific data. They handle the modeling and aggregation of this data, aiding data democratization and self-service data for the business as a whole. This approach enables data to be treated as a product, directly owned by the teams that know the data best and consume it most.

The advantages of this approach are self-evident. Individual departments within an organization can maximize their efficiency by virtue of having a direct conduit to the data they most require. This data remains decentralized, without any barriers to accessibility or issues of unavailability. In this way, the bottlenecks that typically arise from traditional, centralized infrastructure are removed. But while data mesh offers financial services organizations a chance to maximize the full potential of gathered data, it is important to ensure that no mistakes are made in its implementation. 

An innovative approach to data handling lies at the heart of this issue. However, financial services organizations must not overlook standards of governance and compliance in their quest for efficiency. The financial sphere is held to strict regulatory standards, with numerous governmental and industry bodies overseeing the industry. Financial services organizations need to find a balance between efficient data management, safeguarding gathered information, and maintaining consumer trust. These factors all need to be considered when implementing a data mesh strategy, in order to maintain compliance with the latest legal and industry frameworks. 

Maintaining interoperability between the domains of different financial services organizations is another important factor to consider. This is achieved through data virtualization, which creates a logical layer between siloed data sources and domain-specific data consumers. 

With data virtualization, users can access the data they need at the time of their choosing, with virtually no delay. In contrast, traditional data warehousing and extract, transform, load (ETL) models rely on moving the data from one location to another. By bypassing this process, unnecessary duplication is avoided, bottlenecks are eliminated, and the entire process becomes faster, safer, and more resource-efficient. 

Data virtualization’s logical layer also proves helpful in adhering to data compliance regulations. This is accomplished by automating the enforcement of global security policies, such as by masking sensitive personnel and consumer data and only granting full access to individuals with the correct authorisation.

When all of these factors are taken in conjunction, the vital role of data innovation in financial services organizations is made abundantly clear. Modern architectures such as data mesh play a pivotal role in the future success of businesses in the field. Any company looking to get ahead in this fiercely competitive field must make it a priority to implement these transformational technologies.

Charles Southwood

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Charles Southwood is the Regional Vice President and General Manager of Northern Europe and Africa for Denodo.