This has been a long time coming given that organizations have traditionally organized, managed, and governed data. Traditional models relied upon IT, which often inadvertently resulted in bottlenecks. However, a data mesh strategy allows companies to put more data ownership in the hands of flexible, independent, small, and domain-focused teams.
How your team approaches the challenge of implementing data mesh strategies will make all the difference in how it fairs. Keep these things in mind as you begin your data mesh journey:
1. Start with the end in mind.
Part of your data mesh work strategy should tie toward a subset of business objectives that aim to delight and support internal customers and users. To do that, you must first get a clear understanding of what your customers’ needs are. Then, focus on how you can organize and analyze your data in a way that achieves those goals more efficiently and effectively than your competition.
2. Have the right leadership.
For data mesh architecture to really take off, you need to have leaders who believe in it as a business strategy. Your leadership should expect to continually examine assumptions and rapidly iterate with improvements. You want to prioritize the consumption mechanisms based on how the users are expecting to receive the data. For example, this could mean looking for an effective way to bake machine learning into data products with excellent data integration tools while not sacrificing user-friendliness.
3. Adopt the right mindset.
How? By creating an intuitive user experience (UX) and user interface (UI) and always thinking in terms of prioritizing data as a product. Ask yourself and your team questions such as: What if we interviewed internal consumers like data scientists? What if we created personas and journeys? What if we developed intuitive front-ends that let our internal users easily get the results they need? This sort of questioning can move you toward adopting the right mindset.
4. Bring the organization along.
As data mesh architectures become more prevalent, equal or greater focus should be placed on the end-user experience. Wise managers will make sure teams work carefully with data experts to modify and continue building the best data product possible that are easy — and even delightful — for end users to work with.
Data mesh provides an exciting opportunity in the data world today, and it’s poised to become a dominant model in the coming years. It will continue to evolve with better-defined technologies and refined approaches. Organizations that start now will forge the path ahead and reap the benefits sooner than their competitors — as long as they spend the requisite time on solving “last mile” problems and ensure the platforms they build and deploy are usable internally and externally.
