The world is becoming increasingly digital every day and, as a result, even more data-driven. The datasphere is experiencing stunning growth, with 90% of all data being created over just the past two years. This explosive growth is something that will only continue in the future, and it’s clear that as companies begin to amass more and more data, they need to take a hard look at their data management practices.
With the rapid growth of data, traditional data management practices no longer hold up. The world of data has needed an overhaul; data needs to be instantly accessible, understood, and, most importantly, optimized for businesses to make the smartest and quickest decisions. Data mesh, a modern solution that enables businesses to take control of their data, is a compelling opportunity to solve this dilemma.
What is Data Mesh?
Data mesh is a modern framework developed by Zhamak Dehghani that empowers a company’s individual business units to take control of their respective data and make it accessible to the rest of the company. Overall, data mesh prioritizes decentralized data ownership, the mindset that data is a product, and a standardized, self-service infrastructure to allow data to be shared across the organization.
The key differentiator between a data mesh model and traditional methods is that with data mesh, data is not “dumped” into one place but instead is controlled by the experts. Domain-driven ownership allows each unit to harness its data, allowing them to clean and enrich the data for that specific unit’s goals and purposes and share it “as a product,” subsequently creating a more seamless process for the organization overall. With data mesh, the experts oversee the data which enables them to take advantage of the data in the best way and serve the needs of the company overall.
The Benefits of Data Mesh
Data mesh has the power to expand and evolve with each business and is designed to take the “heavy lifting” related to data operations away from IT teams, creating a more efficient business model for using data. This, in turn, creates a more flexible data ecosystem, as the data systems can advance based on the progress of the business unit. Data mesh empowers the SMEs and supports business agility, but also promotes leveraging a shared framework and a common set of standards to ensure that data is always available, clean, and trustworthy for use, whenever needed. This can create healthier data management skills for an organization—and better data management leads to better business decisions.
Data mesh also uses a self-service infrastructure, which allows the data to be shared across the organization easily. While business units have control of their respective data domains, the entire organization is still cohesive and has a healthy data system. This is because data mesh isolates data complexity to the domain owners while simultaneously reducing friction for data consumers, fostering a deeper understanding of the data on all levels and creating more opportunities for the data to be leveraged. Instead of data being available to only IT professionals and data teams, the entire organization now has access.
Using a data mesh model, data is treated as a product with owners providing ready-to-use data to their consumers in a standard, familiar way. Essentially, this means the data is discoverable, addressable, and trustworthy. By adopting this “data as a product” mindset, companies can ensure that their data is being optimized and used correctly for a specific purpose that fits the organization’s business goals. Like any product, there is a vision and roadmap for how the data should be used and the shared belief that the data should be easily understandable.
How Data Mesh Can Help with Today’s Business Challenges
In today’s data landscape, data is coming from multiple sources. The volume and variety of this data also continues to grow, creating a more complex web and problems for businesses that are still using tools that silo data into one centralized architecture. This creates friction as different business units attempt to understand and optimize data relevant to their units. Data warehouses often require business units to go through multiple different teams to even get access to data, which is an outdated, timely process that weighs down an organization and prevents data from being used in fast, efficient ways to make data-driven decisions. When data gets pumped into one warehouse, the system can be clogged, and the data becomes less decipherable and useful for the business.
By using the right data framework and harnessing the power of data mesh, businesses can thrive in their respective markets and get a better understanding of business goals and what their data is telling them. Each business unit can optimize their data to propel the company forward and increase synergy across units.
The data mesh concept is still relatively new and quite different from what has been the norm in this space for the last decade. How challenging it will be for businesses to transform and transition their data management practices varies greatly with their level of maturity when it comes to data management and data governance. Companies need to adequately prepare and assess their different business units to ensure that it’s the right time for them to begin making the transition. With data mesh, there is no fixed timeframe or deadline; it’s all about what works for each company at different points in their data journey. That’s the beauty of it—not only does it create flexible data ecosystems, data mesh as a concept can be put into place gradually based on what works for each organization.
It’s evident that the datasphere is on the cusp of a management transformation, and data mesh is most certainly part of the future of data.