What Will Predictive Analytics Look Like In 5 Years?

14 October, 2016

Posted by Richard Burdge

When predictive data analytics originally emerged at the beginning of the millennium, only large companies, primarily in the telecoms and finance sector, were able to incorporate predictive analytics tools into their business processes.

When predictive data analytics originally emerged at the beginning of the millennium, only large companies, primarily in the telecoms and finance sector, were able to incorporate predictive analytics tools into their business processes.

The implementation and capabilities of current predictive data tools have progressed significantly to date and will continue to change as user numbers rise and technology continues to evolve.

Expansion of data sources

Effective utilisation of the Internet of Things, including mobile devices like smartphones and wearable technology, will make predictive analytics more accessible for everyday use. Cross-over of data inputs from a variety of sources throughout the day will enable data analytics to become catered specifically for what your customers need, anytime and anywhere. Businesses will be able to minimise resources spent on actively collecting and gathering data, and instead will have the ability to access real-time data where it originated.

Accessibility to businesses of all sizes.

Increasing computer power and the introduction of low-cost SaaS offerings will reduce both costs and waste. Predictive analytics models will become more accessible to smaller businesses and even individuals, avoiding the need for substantial software budgets. Increasing numbers of businesses all over the world will be able to make the most of these tools and predictive analytics will provide this competitive advantage to an ever-growing user base.

Prescriptive analytics

Prescriptive analytics forms the next step in terms of data analysis in business and provides guidance based on both descriptive and predictive analytics results. Prescriptive analytics considers the consequences of multiple possible actions and is able to determine which option is most likely to be successful.

Changing role of data scientists

Originally data scientists were specially hired by businesses to implement and ensure the maintenance of data analytics systems, but the creation of applications which are simpler to use, and the development automated analytical tools will allow a migration of control from data scientists to business users. This means data scientists can focus instead on building more robust and powerful analytics models, and business users can spend more time considering overall businesses problems and goals. As businesses become more confident adopting predictive models, and technologies become more sophisticated, the data analysis market will only continue to grow. Make sure your business is informed about the true value of predictive analytics and is prepared to integrate and embrace Big Data analysis into your business operations.