Q&A: It’s time to level the data playing field

Maximising value from big data relies on scalable tools that are built to be used by the masses, not hobbyist programmers, says Ciaran Dynes, chief product officer at Matillion

From a technical sense, what has enabled the big data movement to infiltrate companies so quickly?

When we think about the technology advancements that coalesce in the big data movement, the biggest one is cloud. It’s the most advanced way we’ve come up with to-date to provide really strong and innovative technology that the vast majority of companies couldn’t have afforded to purchase, build or administer themselves. Without open-source software, there would be no Google, as there would not have been a licensing contract struck with Windows to fund something like Google. It needed Linux and it needed open source. Cloud is not dissimilar. It has provided a different and critically important way of approaching data by enabling a small number of very large and sophisticated companies to provide a commodity that you can sign up to with a credit card and access amazing things.

Technology is only part of the puzzle in unlocking data value. How have historically rigid corporation structures become more open to change?

Traditionally, innovation has been very slow in some large organisations because of a culture of blocking things from being done differently. But when people saw these multi-trillion-dollar enterprises like Google and Facebook emerging, they wanted to jump on the big data bandwagon. Sectors such as retail had little choice because of the threat posed by Amazon, and it cascaded across other industries too. Embracing big data in a meaningful way required cultural change and that came from a board and executive level mandate to do what’s necessary to bring data together. Without that mandate we’d still have these massive silos and fictitious excuses to avoid doing what was necessary to make data useful. Big data forced everybody to change their behaviour and how they managed data.

These are fundamental changes, but what’s still missing in many companies are the skills to do better analytics. How do we overcome this challenge?

If you reflect back on software operating systems in the early 80s, you’ll see the original Silicon Valley CEOs were basically hobbyists. They ordered chips online and built themselves computers. That’s how things got started, but it was never going to be scalable. Then the likes of IBM and Apple came along to build off-the-shelf PCs and democratise access to computing. We now need to see the same happen in how we put together data. It has been a hobbyist’s journey led by people who understand certain programming languages, and we’ve been crying out for technology to advance in a way that democratises the ability of all organisations to make data useful. That’s what we’re building at Matillion: a data operating system that levels the playing field. We’re developing tools for use not only by skilled and hobbyist programmers but by the great masses of people out there. We exploit cloud, AI and all these powerful technologies, but we wrap them in a beautiful, simple user interface that lets every organisation become a successful data company.

Embracing big data in a meaningful way required cultural change and that came from a board and executive level mandate to do what’s necessary to bring data together

How is Matillion’s platform realising the data operating system?

The Matillion platform solves a major problem: it’s really hard to connect all your data; stitching it all together is immensely complicated. We have a unique capability that lets either ourselves, partners or end users – in a no code, drag-and-drop interface – connect to anything. And then the fun begins because you can begin to refine the data, get insights and enrich those insights over time. All those capabilities get you to a point where you have something, visualised simply in an analytics dashboard, that you can truly make use of. Some businesses might be able to build and deploy that once, but how do you maintain it and make sure if it breaks at 3am it can be fixed? The intelligence of a data operating system is such that if any pipelines fail, it can recover, alert or offer an alternative. That’s what takes it from just being a standard solution to something intelligent and self-correcting.

What is the future of data in the enterprise?

We know the value you provide to your customer is everything. In the enterprise of the future, acquiring a customer and retaining a customer are vastly different things. The intersection of data and innovation is critical to fostering better customer relationships. But there’s a step further. The really great companies today take their data and share it with their partners because they recognise they’re not just standalone businesses. They’ve got to combine with an ecosystem of partners to provide a modern digital experience. Amazon does this really effectively, sharing insights and data about customers and buying behaviour, and that’s why they have an unparalleled service and their partners come back for more. So if you’re going to provide amazing first-class customer experiences, it’s the intersection of data, innovation and partners. That’s what the modern enterprise is about.

Learn more about Matillion at matillion.com/demo

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