- October 15, 2021
- Posted by: Aanchal Iyer
- Categories: Artificial Intelligence, Predictive Analytics
Prescriptive Analytics – The Future of Big Data
Big Data has bought in an era of data analytics that is continuously taking different forms and one of those forms is “prescriptive analytics”. This type of business analytics helps one find the best approach for a particular circumstance. Prescriptive analytics is also considered as the third or final part of business analytics, which also incorporates both descriptive and predictive analytics. Prescriptive analytics utilizes descriptive analytics and predictive analytics to derive ideal results or solutions from helping one resolve business problems and it is driving the future of big data.
Differences Between Predictive Analytics and Prescriptive Analytics
Raw data is abundant in today’s digital age. About 90 percent of today’s online data signifies a compilation of data that was created in a few years and it is expected to grow rapidly. However, one must understand that this raw data does not have value on its own. The raw data needs to be processed in a manner that it offers insights that are valuable to an organization for it to be resourceful. With raw data, one can identify and recognize patterns, create models based on these patterns and other known information, and make data-driven projections to resolve business issues.
Both predictive analytics and prescriptive analytics enable one to convert primary data into useful insights. However, predictive analytics and prescriptive analytics vary in the type of insights one can leverage. Predictive analytics enables one to make predictions depending on prevailing and current data. It allows one to use the identified raw data and process it in a way, so that it can be used to make predictions on the data that you do not know. With prescriptive analytics, one cannot only make sense of raw data but also use that data to understand the actions to take immediately. It utilizes Machine Learning, simulations, and mathematical optimization to enable enterprise leaders to make better-informed, data-driven decisions.
When there are several options to choose from, prescriptive analytics helps to identify the best outcome or solution based on known scenarios and limitations.
Prescriptive Analytics Has Various Big Data Advantages
Prescriptive analytics comes with some benefits you can utilize with Big Data, such as improved awareness of the impact of new techniques or technologies, enhanced utilization of resources and improved insight into habits and patterns of customers. For example, one can use prescriptive analytics to understand the best social media engagement opportunities one can undertake.
Prescriptive analytics is now being used successfully in a number of businesses. General Electric (GE) and Pitney Bowes forged an alliance to utilize prescriptive analytics using data produced from Pitney Bowes’ production mailing and shipping machines. GE has developed personalized applications for Asset Performance Management (APM) for Pitney Bowes, using its Pedix software platform so that Pitney Bowes could provide job scheduling capabilities, productivity, and client services to its enterprise clients.
Prescriptive Analytics Will Change the Future of Big Data for Business
The future of prescriptive analytics will ease the analytical development for automated analytics even more, where it will replace the requirement for human decision-making with automatic decision-making for businesses. For example, automated analytics will be able to leverage applications to select the best marketing email to send to customers instead of relying on a marketing director to decide on this.
With its augmented use and value, prescriptive analytics is driving the future of Big Data. Enterprise leaders can avert risky business moves and decrease financial losses by leveraging prescriptive analytics to evolve the logic of their business decisions.