Current data architecture is going through a revolution. Enterprises are starting to shift away from the monolithic data lake towards something less centralized: data mesh. It’s a relatively new concept, first coined in 2019, that addresses potential issues with data warehouses and data lakes that can cause businesses to be slow, unresponsive, or even suffer from data silos. What is a data mesh, and how could it benefit your business?

The world is full of different types of goals. Consider football. The goal in football is at the end of the field. A runner either crosses the goal or they don't, when trying to make a touchdown. Or, consider basketball. In basketball, when a player shoots the ball, the player’s shot either goes through the net or it doesn’t. Alternatively, consider ice hockey. When a hockey player shoots the puck, it either goes into the net — or it doesn’t.

With the ever-increasing volume of data being generated from a highly diverse set of data sources, organizations have started to increasingly direct their focus on solutions that can help them with data management more efficiently and effectively. Indeed, in the current decade, having a robust data infrastructure is key to an organization’s success, and timely data-driven decision-making is what every management is striving for today.

Data warehousing requires data centralization, whereas data mesh enables a decentralized approach to data access. Organizations might think that the solution to their data management strategy requires a choice between the two, but the reality is that both approaches can and should co-exist.

Irrespective of what it’s called, the market has talked about what amounts to data mesh for several years. The concept of decentralized data management that is driven by business domains helps support the need for business-focused data outcomes. It also helps place value on where the value of data projects should be - on business needs. Data driven organizations need to look at business domains as a way of organizing the various desired outcomes of analytics and data movement initiatives.

Current data architecture is going through a revolution. Enterprises are starting to shift away from the monolithic data lake towards something less centralized: data mesh. Data mesh is a relatively new concept, first coined in 2019, that addresses potential issues with data warehouses and data lakes that can cause businesses to be slow, unresponsive, or even suffer from data silos. Data mesh benefits are able to provide a wealth of advantages to your business.

Data mesh is being talked about a lot to describe the way data is managed across the organization. But what does it really mean for your organization’s data management strategy and how can its framework support your business needs and drive data pipeline success? On a high level, data mesh is about connecting and enabling data management across distributed systems.

Organizations worldwide put their best foot forward to create a centralized database where information is gathered, stored, and managed. Their data engineers transform difficult-to-decipher datasets into data pipelines that can be used by data scientists, analysts, and consumers. However, the new data mesh concept championed by Zhamak Dehghani, the director of technology for IT consultancy firm ThoughtWorks, allows domain teams to conduct cross-domain data analysis independently.

Data teams have the impossible task of delivering everything (data and workloads) everywhere (on premise and in all clouds) all at once (with little to no latency). They are being bombarded with literature about seemingly independent new trends like data mesh and data fabric while dealing with the reality of having to work with hybrid architectures. Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem.