Predictive Analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. It analyzes current and historical facts and situations to make predictions about future or otherwise unknown events.
Simply put, Predictive Analytics combined with AI are prediction machines.
With large behavioral datasets becoming increasingly available, the future of Predictive Analytics coupled with Artificial Intelligence and Machine Learning will give rise to a new generation of applications that will, with increasing accuracy, predict the way we live, work, and play. Here are some of our predictions for the future of Predictive Analytics:
1. Outcome-based applications
As with the advent of new forms of technologies, early adopters tend to trend towards being purists — providing solutions with minimal customization and application to real-world situations. Particularly where the understanding of Predictive Analytics and its capabilities is low, most Predictive Analytics solutions providers provide data analytics solutions with common applications like consumer spending analytics and healthcare cohort analytics.
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However, with more competition and growth within the market, a variety of applications will emerge, with solutions and engines being purposed for real-world outcomes, including improving productivity, reducing organizational costs, preventing movements within markets and a host of other use-cases.
We have seen, through our own experiences with Cognitive Artificial Intelligence, that applications of new technologies become increasingly outcome-based, and with democratization of such applications of Predictive Analytics becoming commonplace, the cost per implementation reduces significantly.
2. The integration of sensor-driven data
Almost quietly, the world has embraced the Internet of Things exponentially and at the time of writing this article, we have over 21.5 billion interconnected devices in service at any given time.
John Chambers of Cisco fame has predicted that we will move from the Internet of Things to the Internet of Everything; where the Internet of Everything (IoE) brings together people, process, data, and things to make networked connections more relevant and valuable than ever before. This IoE will turn information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries.
With humanity moving towards a world of hyperconnectivity, the growth of Predictive Analytics will be mired with increasing cybersecurity and data privacy requirements. That said, it is my belief that the growth of sensor-driven data will only grow the hyper-localization and personalization of Predictive Analytics.
3. Increasingly powerful data visualization
One of the ubiquitous challenges of data analytics in today’s current world is the walled world of data scientists. As Predictive Analytics becomes part of our everyday existence, we predict a growth in the need for data visualization — or, people who translate the minds of data scientists into understandable bite-sized chunks. The future of Big Data Visualization will dramatically improve effectiveness and efficiencies through real-time immersive visuals, helping business leaders make important decision through valuable insights.
With the march towards improvements in AR/VR, the sky’s the limit for the growth of immersive data visualizations.
4. Personalization at scale
The race is heating up with current applications of Big Data Analytics to create personalization at scale for sales and marketing solutions. With Predictive Analytics propelling Big Data forward, I believe we will achieve personalization at scale quickly, for a multitude of applications apart from consumer spending.
It is my view that our lives will be transformed on a personal level in the way we live, work, and play through Predictive Analytics — in a future where the proverbial data-backed crystal ball can help humanity to think, act, and do better.