When you unlock the power of data, you can deliver entirely new products, services, and revenue streams. But getting there requires some essential building blocks – starting with the right data platform. 

At Zühlke, we often talk about the power of data ecosystems – of harnessing cross-company data sharing to develop new, previously impossible solutions. But let’s take a step back. You can’t build a town without first building a house. Before you can reap the rewards of a data ecosystem, you need an effective internal data platform as your foundation. 

Data platforms are the building blocks of true data-sharing empowerment. But they require  companies to curate a culture of data literacy and transparency. Here’s how to accelerate time to value with the right data platform and mindset. 

What is a data platform? 

At their simplest, data platforms are databases that span and combine multiple sets of information. That interoperability helps businesses to develop new value propositions, with data at the heart of things, rather than as an afterthought. 

In this way, data becomes an enabler for innovation. ‘When you make a data platform, you’re effectively ingesting multiple data types and putting them on a very large disk’, says Zühlke UK’s Head of Data and AI, Dan Klein. 

‘The crucial thing is what you do with the tooling you put on top of that disk’, he explains, ‘as that tooling is what allows you to democratise data across your business’. 

As such, modern data platforms are the antidote to more antiquated ways of storing data – namely, in individual siloes. SQL, for example, is a really efficient standard for storing specific, structured data for one intended application. But it’s limited if you want to use that data for (or with) anything else.  

A data integration platform turns that one-way cul-de-sac into an interconnected highway, accessible across departments. 

‘Suddenly you'll have really powerful data that’s no longer highly constrained to a single use case – and you can build as many applications as you like on top of it’. 

So why does this matter? And what, in practice, does a data platform enable you to do? 

Why are data platforms important? 

Data platforms are the building blocks in an innovation ecosystem – where diverse organisations exchange data and resources to co-create a superior customer value proposition.  

But a platform has much more immediate internal effects – with real-world business benefits. 

The only problem? It’s often impossible to predict exactly what those use cases might look like before you start making data connections. Sometimes you might land on more streamlined processes, but sometimes it might be entirely new ways of working, or even brand-new products and services. 

‘The challenge historically with the business case for platforms has been that you don't know what you don't know’, Dan explains. ‘So until you join that data together, you probably won't realise the value of doing so.  

‘Because of that, we often find that it’s useful to demonstrate to business leaders what prototyping “joining the data together” actually looks like to prove the value of doing exactly this’. 

But while the exact outcomes for each organisation are different, the myriad use cases for these platforms across industries are, in general, much less finger-in-the-air. 

‘It’s key to prototype and prove to business stakeholders the true value of connecting diverse datasets’. 

For example, think about ‘Single Customer View’. Businesses that rely on individual databases, often languishing in spreadsheets, won’t be able to piece together any useful insight into customer behaviour. But with a modern platform in place, they’ll be able to draw powerful conclusions and actions from customer behaviour across channels and touchpoints.  

The Zühlke-made NHS COVID-19 tracking app is another data platform success story. The app helped the UK government collect millions of data points, but what made it useful was the interoperability of that data. This allowed for multiple use cases – from telling users they may need to self-isolate, to mapping the disease’s spread. 

Dan offers another example: international shipping. ‘An average container ship these days probably has up to 30,000 sensors on it. But what can you do with all that data? A lot of these sensors have historically done really specific jobs. But if you link all the sensors together within a platform, you have a much better understanding of ship maintenance and part longevity overall. So that means you can dock a ship to fix or replace multiple parts at once – rather than ad hoc as individual parts wear out’. 

‘Generally’, he adds, ‘our aim is to find one use case that can justify doing this work. What usually happens then is that once businesses link their data together, they naturally find a wide range of other applications as a result’. 

What’s the process? 

Getting to that stage requires something of a mindset shift: the first step to building a data platform is to foster a culture of data literacy within a given business.  

That doesn’t mean that everyone has to become a data scientist, it just means that you need to create a robust dialogue between business and technical teams.  

‘When you create a common language and understanding between data specialists and business users, your organisation will be in a better place to make better use of data analytics’. 

Then, with that culture embedded, we can begin to run through four key steps that build up as foundational layers: 

1. Ingesting raw data
2. Validation
3. Adding controls
4. Linking data sets 

‘Ingesting’ simply means collecting as much raw data from across the business as possible. This can be structured or unstructured, images, text, or values. That raw data then needs to be checked and validated. Is anything missing? Is anything clearly erroneous? Does it all make sense? 

Once those checks are completed, you add a layer of control to determine who can access what data, and determine any privacy and security regulations that need to be applied as a result. Then you’ll look for ways to link the data and turn those links into a front end that can be accessed by various teams across the business. The resulting tool is your data platform.  

There’s no telling what that tool will enable for each business, but building a platform will always result in efficiency wins.  

Why democratised data is a business imperative 

At Zühlke, we believe that this internal data democratisation is a modern business imperative; data needs to be freed and linked in order to empower decision-making, enable new value creation, and enable you to solve problems with emergent solutions.  

AI is a great example here. Any application powered by artificial intelligence needs robust data access to function. So any business hoping to make use of AI needs to have a forward-thinking attitude to data sharing. 

In that way, data literate organisations allow people to move away from traditional, limiting tools like spreadsheets and begin benefitting from access to richer information and insight.  

Ultimately, data platforms act as the foundations underpinning those benefits.  

Speak to us today about how you can create new value at scale with the right data strategy, platform, and people-centred AI solutions.