2016: Cloud, Big Data & Predictive Analytics Converge
By Vikram Nanda
It’s still early in 2016, but a few trends are already forming for this year. Some of these trends build on systems and knowledge already known, but with new uses.
This year we’re already seeing a convergence trend that mixes cloud, Big Data and Predictive Analytics to deliver data and Business Intelligence in real-time. As more organizations become comfortable with cloud technology, they are starting to look at it as a more viable way to deploy their tools. They are realizing they can have the same security and performance, but with greater scalability than with traditional systems. In fact, many organizations are coming to the conclusion that cloud offerings offer multiple security certifications that are demanded by industry regulations that are too costly to replicate internally, reducing the burden on IT departments and free up valuable resources. Furthermore, organizations realize they can use the cloud to remotely access their information and track data in real-time. A good example of this is how John Deere uses cloud technology to track seed and hay output in real-time from their tractors.
In a CIO Magazine article titled, ”Study reveals that most companies are failing at Big Data,” it’s being reported that “a quarter of C-suite executives report not seeing any value from data around decision-making, product development, cost savings or customer acquisition and retention.”
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More organizations are realizing how cloud technologies are contributing to the exponential growth in the volume of data. Not only is the volume of data growing, but the type of data available that was previously not accessible is now at an organizations’ fingertips. Some of that new data includes machine-to-machine, Internet-to-Internet and social media data, while also analyzing unstructured data and extracting valuable analytics.
Every year analytics become more sophisticated, and with that we have seen the rise of and use of Predictive Analytics across industries. One of the use cases of Predictive Analysis is to help businesses pinpoint a client’s propensity to act. By using both internal and third-party data, predictive models can be built to help organizations more effectively plan marketing campaigns, increase revenue per customer, stop fraudulent activity, prioritize debt collections and improve operational processes.
But just because organizations can process and store all this new data, it doesn’t necessarily mean the information is important to managing business functions and achieving objectives. This is where data quality comes in. The challenge is how to gain access and insight into the data that is relevant and ensure that it’s acted upon. By synthesizing real-time data from the cloud, 3rd party data and internal systems, an organization can yield more accurate insight to predict the opportune time to upsell or cross-sell to maximize campaign ROI. By integrating company data and customer experience, organizations can serve their customers better and with less effort.
Another trend that has carried over from 2015 is the breaking of barriers between IT and other parts of the organization. Today, IT teams are closer than ever with other business departments. There has been an increase in IT type roles across various business units within organizations. As a result, more companies are creating the position of Chief Data Officer (CDO). This C-suite position architects a strategic direction and works with the business department to clearly articulate the business objectives and ferret out data needs, while working with the IT department on accessing it. The new role will have a strict business focus to help organizations create new business strategies based on analytics and data to help increase sales and improve operational efficiencies within the organization. The CDO role will break down political barriers between disparate data silos and ensure staff has the tools and skills needed to analyze, understand and implement insights.
Vikram Nanda is the Senior Principal of Strategic Services at Infogix. Vikram joined Infogix in 2013. Over the last 17 years, he has led multiple advisory and software implementation initiatives for multiple clients. Vikram has a Bachelor of Technology in Engineering from Punjab Technical University, India, and an MBA from The University of Chicago. Connect with Vikram on LinkedIn.