As data continues to dominate the digital transformation landscape, we are flooded by terms such as data mesh, data fabric and data lake. We are hearing much more about these concepts and now companies are starting to realise how popular and significant they are becoming. In fact, Gartner even named data fabric among its top strategic technology trends for 2022. So let’s take a look at what data mesh is and how it can be used across a range of industries like manufacturing, retail and financial services.
We can use a simple cooking analogy to help explain the data mesh concept. Imagine a chef wants to cook with fresh ingredients; in order to make the dish, the chef combines different ingredients to ensure that the dish is more than just a sum of its parts. Now, when mixed together, this great dish is better than what we’d expect from the individual ingredients, because the way they complement each other adds to the quality. This applies to data too.
Companies want to work with fresh, real-time, data, but are often limited by a siloed approach to it. If we continue with the cooking analogy, it’s as if companies were limited to using individual ingredients without ever mixing them, resulting in a less creative outcome.
As with any data approach, for data mixology the biggest challenge is data sharing. Siloed systems are still common and despite organisations trying to solve the issue by implementing data warehouses or data lakes, they keep struggling with slow, costly and difficult to maintain solutions that just haven’t hit the spot.
The ideal scenario is for businesses to have a central location where all data can be stored and accessed by everyone across the organisation, so it can be shared, analysed, and drive business value. Where data mesh stands out is the way it supports mixology and synergy. It’s as if data meshes allow us to make the data equivalent of duck a l’orange, goan fish curry or Bloody Mary. The beauty is in the mix.
Data mesh is based on four principles: domain-driven ownership of data, data as a product, self-serve data platforms, and federated computational governance. In the words of a chef, this means ingredients are in the kitchen, and they’re of the highest quality and ethically sourced. We can now design the dish we want and mix the ingredients with the confidence that we’ll create an exceptional customer experience.
Data truly is at the heart of every modern business, but only by creating synergies can companies unlock the full potential of data.
Historically, data was used to serve a product or solution. Take a customer relationship management platform, for example: the data’s sole purpose was to serve that platform. However, what we are seeing now is a shift in this relationship. Products or business solutions are now creating data, which can become a product in itself. Therefore, instead of data serving the solution, the solution serves the data. If we contextualise this data, we can create new “dishes” and drive new business models.
If we take the banking industry as an example, banks are seeking ways to become more relevant to today’s customers. Real-time push notifications first offered by challenger banks are now considered a must. Traditional banks need to offer additional intelligence enabled by data, such as tracking finance and support in budget planning, based on past buying patterns and life objectives.
For mobility companies such as Uber, being able to communicate location, traffic information, driving styles, estimated arrival, pick up point and destination, in real time are all core elements of the business. This info can all be combined to create a payment when the trip is complete and capture customer feedback.
In retail, businesses desire to merge data from website interaction, mobile apps and in-store experiences, so they can offer real-time, contextualised and highly targeted offers. Moreover, they can capture post-sale feedback and returns, or further upsell and cross-sell products and services.
While developing a digital transformation strategy that fully leverages the value provided by a data mesh isn’t easy, many businesses are waking up to the fact this is essential. Getting it right means that companies can leverage the power of the network effect to drive further data synergies. As more parts of the business consume the various data sources, they will produce more data, which in turn results in more data consumption. In other words, we have the ingredients, now we need the recipes.
Lyndon Hedderly is director of customer solutions at Confluent
Subscribe to our Editor's weekly newsletter
Share
