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Modern data stacks: the decoupled approach that can benefit your business

As monolithic architectures give way to flexible, granular data meshes, explore the modern data stack, data-driven business & the changing role of consultancies.

As businesses shift to align with customer expectations, so too do the technological and analytical architectures that power them. Monolithic systems have given way to dynamic, fine-grained, modular structures. This is the modern data stack; encompassing a vast landscape of technologies, frameworks and systems, often powered by Artificial Intelligence and Machine Learning.

The monolithic data stack was once the de facto choice for organisations. The ability to buy everything necessary from a single vendor was seen as the ideal way to simplify business intelligence stacks and ensure that all those various systems ran in harmony.

That’s no longer the case. For future-facing businesses that need to evolve alongside their customers and thrive to drive their data culture and data literacy, incorporating flexibility, granularity, and self-service capabilities into their tech stack helps them to do so.

Powering this change is a paradigm shift towards product thinking and decentralised ownership.

Product thinking ensures that the business outcomes and user experience of a solution are its driving force – not just ‘providing’ some data. Enabling an evolution-ready product with documentation and reliability is another cornerstone of the approach, with the necessary technology and expertise in place to tackle future adaptation.

Coupled with this is decentralised ownership, whereby specific data is owned by business-specialist individuals and teams, all working towards a central goal. This model means that data is handled by the teams closest to it, minimising reliance on central IT to understand, translate and provide this information. Data becomes an asset, driving progress through all involved.

These firmly place emphasis on selecting the very best architecture and tools for each specific data product and processing task, reflecting a culture that needs to move to a more decentralised, specialist approach.

Exploring the modern data stack

So what are the key characteristics of a modern data stack?

  • The ability to handle data volumes and infrastructure concerns – a malleable, responsive data stack architecture that can work with, and adapt to, infrastructure changes and the massive volume of data.
  • Analytics with an end-user focus – transparency and accountability baked in, allowing performance, value and workflows to be objectively assessed, driving data culture through self-service capabilities.
  • The incorporation of AI – the use of intelligent systems that can learn, assimilate data points and become more efficient as they operate.

Data itself is also a key part of the modern data stack. As organisations seek more valuable insights from their systems, access to diverse data sets – both internal and external – is essential. As is a system that can make sense of those disparate data sources and deliver clear insight.

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The data-driven organisation

The characteristics of the modern data stack are central to data-driven organisations, which look to make informed, data-backed decisions, rather than relying solely on intuition or slow manual reporting. Established within larger enterprises, this strategy is now accessible to smaller organisations and individual departments too, owing to the capabilities of granular data stacks.

The shift to data-driven strategy is also due to many leaving behind the limitations of traditional, monolithic approaches. Vast data lakes that were born from universal systems quickly became data swamps, due to the difficulties of maintaining a centralised understanding of all that data, and the processes to manage it.

This has paved the way for the ‘data mesh’, which promotes a decentralised organisational structure for data. The use of a data mesh brings clarity to the challenge of muddled domain understanding – and negates the risk of data swamps.

How we can help

The move towards modern, decentralised data stacks and the use of data mesh also has implications for the role of technology consultancies, whose goals are no longer purely technical, but organisational and structural too.

Modern data stacks and the use of AI in software development makes one thing abundantly clear: the need to embrace a decentralised approach to data processing.

The journey from monolithic architectures to data meshes backed by a modern tech stack isn’t a straightforward one. And it’s here that consultancies with their finger on the pulse can make all the difference. By steering clients through the technology and strategy changes they need to become data-driven, they can set them up to gather, organise and take action from diverse data sources, see significant impact and deliver unique experiences to their customers.

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