Spurred by IoT, analytics at the edge becomes the new normal. Thanks largely to advancements in modern data technology, more organisations than ever before are putting the right data on the right platform for the right reason.
This new level of data efficiency greatly reduces – and, in the long run, may ultimately eliminate – the need to pull data in to a centralised source such as a data warehouse or analytic sandbox for the purpose of analytics.
Instead, given the distributed nature of connected devices and the explosive growth of IoT infrastructures, more organisations will look to execute analytics at the edge, and, as a result, the ability to push analytic capabilities to (and run them directly at) the source of data will become paramount. Applying a predictive model and running the analytics where the data lives eliminates the time, bandwidth and expense required to transport the data, enabling immediate action to be taken in response to the insight.
The growth of IoT, in particular, will spur this movement of analytics out to the edge. We now have the ability to harness and use IoT data at the speed of business in an economic way, such that in some instances, transporting that data back to a centralised core is both inefficient and untimely. The power of IoT ultimately lies with the ability to analyse data and move at the real-time speed of a specific workflow. Analytics at the edge makes that possible.
The role of the ‘Citizen Data Scientist’ will continue to expand and evolve
We are starting see a new breed of analytics users cropping up throughout organisations everywhere. Citizen data scientists — or every day, non-technical users — are going to play an even greater role in the analytics revolution as platforms will begin incorporating technologies and capabilities that help these users consume analytics in an easily digestible way.
This new wave of business-savvy users will also present challenges: Citizen data scientists will experience a learning curve in wrangling data, running the optimised analytic and presenting the outcome of those insights. They’ll also put the onus on vendors to deliver quick-start analytics template and reusable workflows. Once the learning curve is overcome and the right capabilities are delivered, citizen data scientists will be the driving force behind the use of analytics to drive innovation.
Analytics will most significantly affect vertical markets, especially manufacturing
One could already argue that the ROI of advanced analytics is highest when applied to targeted, vertical market use cases. This will continue to be the case in 2016 and beyond, with manufacturing – particularly regulated manufacturing – leading the way.
Within regulated manufacturing, not only are there numerous processes that can greatly impact the precision and quality of a given production run, but outcomes often need to be validated and proven to meet the regulations of the industry being served. As such, advanced analytics platforms will be increasingly relied on not only to uncover insights that help optimise processes, but to verify and validate those insights in accordance with regulatory requirements.
So, for example, a pharmaceutical manufacturer might leverage advanced analytics to optimise the drug creation process and avoid a catastrophic batch loss, while also using advanced analytics tooling to confirm that its processes have been tested and validated as required by its governing regulatory body.
All innovation will trace back to analytics
At its core, advanced analytics helps companies better serve their customers through new innovations. Many already create new products and services based on insights gleaned from data. Others use analytics to fundamentally alter the way they service customers and improve the customer experience.
This trend will grow exponentially as organisations continue to realise the true value in leveraging predictive analytics. Service departments will have the ability to take prescribed actions in advanced of an issue occurring. Doctors will increasingly run analytics to offer precision healthcare and personalised medicine that better serves patients. Patients themselves will bring their own data to the table, creating a whole new layer of both challenges and opportunities for data-driven leaders.
This trend of data-driven analytics advancing each and every aspect of the business – from inception to completion – will only continue to evolve. Ultimately, all forms of innovation will trace back to analytics in some manner or another.
Todd O’Brien, head of sales, advanced analytics, Dell Software
Image credit: Shutterstock/Sergey Nivens