As we look to what lies ahead for the big data industry in 2017, what will be the main challenges for marketers? This article combines the thoughts of three leading experts from Camelot Global, NHS and Think Big on what the biggest challenges, changes and impact will be for big data in 2017.
The three commentators in this article are:
• Tim Seears, VP emerging technology at Think Big, a Teradata Company
• Jon Everitt, group data architect, Camelot Global
• Daniel Ray, director of data science, NHS
(Pictured in order above)
In the last few years, big data and data analytics have gone from being flash in the pan buzzwords to a core component of commerce influencing day to day life of consumers around the world. And you don’t have to look far for examples of its successful deployment in practice. They were used to inform decisions in Donald Trump’s election campaign – and we know how well that worked out, while brands such as Amazon is harnessing the power of data to help streamline, plan and execute the monumental task of goods delivery around Christmas.
But all the experts agree that we have just scratched the surface of possibility and, for all the advancements made in this space, there is a long way to go to unleash it’s potential. So to get an idea of what is in store, we caught up with three leading experts to hear their views on what the biggest challenges, changes and impact will be for big data in 2017. Here are the views of; Jon Everitt, group data architect, Camelot Global, Daniel Ray, director of data science, NHS and Tim Seears, VP emerging technology at Think Big, a Teradata Company,:
What will be the biggest challenge for the big data industry in 2017?
Jon Everitt: “The nirvana of big data is to bring together disparate data sources and provide data scientists with the ability to model them into something incredibly useful. This means looking at huge amounts of raw data, juxtaposed against three main pillars; governance, quality and security. The issue we will see is how businesses balance the objectives of data freedom against a corporate background that has traditionally had stringent parameters around its usage.”
Daniel Ray: “Governance will become a bigger focus point than big data technology solutions. It’s essential that all organisations using public records follow and comply with correct governance. We can’t lock up everyone’s data, so no one has access to anything. But on the other end of the spectrum, you’ve got everyone being able to see everyone’s data in order to use analysis for the common good. It’s a balance in ensuring data is safe and secure so that we’ve got the public’s trust, and in being able to use that data to add value and understanding to planning, variability and the inequalities that may exist today. If we can follow and comply with correct governance and maintain public trust, we can use big data in the right way to improve care. Being transparent and communicating effectively is a big priority – now, and going forward.”
Tim Seears: “Without a doubt, productionising analytics is going be a huge challenge next year. By this I mean, the process of bringing analytics and model management into production in a repeatable way. People are moving out of the PoC phase and into production and are not ready for the challenges this poses. They need production ready systems, and this is what Kylo, our unique data lake accelerator, has been designed to address.”
What will be the biggest change in the big data industry in 2017?
Jon Everitt: “The biggest change we will see is more real use cases, specifically in the areas of production and operation. The technology architecture is also evolving rapidly, and this is something that is likely to accelerate the time it takes to identify credible business insights and getting them live. We’re already in the process of moving from months to days and even hours, and next year, we’ll begin to see a real correlation between big data platforms and business results.”
Daniel Ray: The cognitive AI space will also continue to progress in 2017. The evolution will be twofold. Firstly, we’ll progress in our ability to use big data algorithms at the point of care to influence when and how decisions can be made. Secondly, this will enable us to make longer term predictions on health and disease that we can identify via big data, using for example, data collected against all patients who develop dementia. This will change the future of doctors. You will never replace the doctor/patient interaction, but we’ll start using computers more to do what they are good at, which is pulling in lots of sources of information and being consistent. It will allow doctors to focus on baseline medicine more.
Tim Seears: “A lot of people are moving from PoC into production. Another change is that more companies are actually beginning to realise value from their big data investments and applying that knowledge in new ways. This means it’s going to be an exciting year.”
What area of business will see the biggest impact from big data in 2017 and beyond?
Jon Everitt: “While there have been huge advances in big data adoption in areas of business like production and operations, there is still much work to do. There are still countless examples where this is in place, but failing – a prime example of this being pushing adverts for toys to parents in the months after Christmas. It is here where we will see the greatest movement next year, continuing to refine processes where elements where human psychology has less of a role to play. There is also lots to do in the marketing department but, equally, there are lots of challenges, which is leading to the rise of behavioural scientists.”
Daniel Ray: Security will become more important than ever in healthcare and big data analytics. In order to innovate, you’ve got to move into the unknown, which carries a certain level of risk. It’s about pushing the boundaries to be able to innovate, but doing it hand in hand with governance, but not so far as to alienate people and lose their trust. If we don’t innovate, we’d never move forward, but we need to do it whilst maintaining transparency, engagement and trust. In this sense, the governance part of building technology will take longer and be more complicated than the initial technology solutions. We can easily build a tool that enables all levels of healthcare professional to query databases and get results against public healthcare records, but it’s much harder to build in that governance to ensure people are only seeing the records they should be seeing.
Tim Seears: “There is still lots of ground to be made in some the areas of business that have already taken tentative steps into big data. This will mean more developments in the fields of operations and supply chain optimisation.”
It’s clear from hearing the views of Jon, Daniel and Tim that big data and its industry use cases are on the cusp of a game-changing period. Yet, for all the excitement over what is possible, there remains issues regarding privacy and security to name but a few. However, while these are clearly very important challenges to address, you get the impression from hearing the views of such engaged and informed industry experts, that there is no challenge to big when it comes to unleashing the potential of big data.
Tim Seears, VP emerging technology at Think Big, a Teradata Company
Jon Everitt, group data architect, Camelot Global
Daniel Ray, director of data science, NHS