Don’t trip up on the edge of innovation


Innovation used to happen in structured cycles. The new invention was often a planned event and the domain of a select few departments within an organisation.

But in today's always-on economy enterprises need to innovate on a continuous basis to keep up with new players that base their entire businesses on data and algorithms. Deliveroo and Uber are great examples of this.

To keep up with these new players, enterprises appreciate that innovation is most potent when it’s enabled at the edge – where the enterprise meets the outside world. Yet the speed of data creation, and the new sources and types of data that our hyper-connected world is creating, require more powerful analytics and algorithms than ever before. Why? Because business need to dig into the richness of this new data landscape to better understand what the data is really telling them.

Consequently, lines of business (LOBs) are creating a hybrid approach to analytic and algorithmic evolution. How? Data citizens within LOB functions are mixing open-source coding capabilities with solutions from independent software vendors (ISVs).

Is this a business risk or business advantage? It depends on how you bring everything together. Rather than buy multiple capabilities or use open source analytics – whether for traditional analytics, reporting, visualisation or to drive machine learning – businesses that want to push the boundaries of innovation should think about how to unify their analytic capabilities and data management engine. It can’t be a piecemeal approach that gets built up into a complicated mix over time. Otherwise, IT complexity and cost could end up stalling their ability to drive competitive advantage, revenue growth, effectiveness or customer satisfaction – tripping them up in the race to push innovation.

However your organisation chooses to collaborate and use data for innovation, SAS’ new cloud-based, open platform can power the future of your analytics, whether you code in Python, Lua or other languages. Find out more about SAS Viya.

You can also find out how organisations across the UK and Ireland are balancing open source technology and ISV solutions.


About Author

Peter Pugh-Jones

Head of Operations, EMEA & APAC, Global IoT Division, SAS

Peter Pugh-Jones leads a team of expert industry consultants across EMEA & APAC for the global IoT division at SAS. During a career spanning four decades, he has been lucky enough to have worked all over the world in diverse roles and sectors of the technology and software industries. A passionate believer of utilising the right tools and technology to meet the data and analytical challenges of the present day, Pete or PPJ considers himself a lifelong learner with an optimistic view of the future of technology and the adoption of artificial intelligence to improve quality of life and sustainability. Pete is driven by a sense of responsibility to ensure his customers derive the very best return on their investments in digital transformation technologies. With the convergence of robotics, analytics, artificial intelligence and IoT on the cusp of this fourth industrial revolution, Pete firmly believes there has never been a more exciting or important time to be working in the advanced analytics space as we begin the journey to operationalise AI and transform all our lives for the better.

1 Comment


    Hello Peter,

    This article was excellent with Advanced SAS analytics, We are learning , leading using with different scripting language in our day to day Product & Strategy , business objects Business intelligence concept ! Regards Asish

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