Predictive Analytics Essay

Wednesday, January 19, 2022 5:28:40 PM

Predictive Analytics Essay

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Descriptive vs Predictive vs Prescriptive Analytics

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Learning Analytics is not simply about collecting data from learners, but about finding meaning in the data in order to improve future learning. To do this, learning analytics relies on a number of analytical methods: descriptive analytics , diagnostic analytics, predictive analytics, and prescriptive analytics. Predictive Analytics is a statistical method that utilizes algorithms and machine learning to identify trends in data and predict future behaviors. With increasing pressure to show a return on investment ROI for implementing learning analytics, it is no longer enough for a business to simply show how learners performed or how they interacted with learning content.

It is now desirable to go beyond descriptive analytics and gain insight into whether training initiatives are working and how they can be improved. Predictive Analytics can take both past and current data and offer predictions of what could happen in the future. This identification of possible risks or opportunities enables businesses to take actionable intervention in order to improve future learning initiatives. For online learning specifically, predictive analytics is often found incorporated in the Learning Management System LMS , but can also be purchased separately as specialized software. For the learner, predictive forecasting could be as simple as a dashboard located on the main screen after logging in to access a course.

Analyzing data from past and current progress, visual indicators in the dashboard could be provided to signal whether the employee was on track with training requirements. At the business level, an LMS system with predictive analytic capability can help improve decision-making by offering in-depth insight to strategic questions and concerns. This could range from anything to course enrolment, to course completion rates, to employee performance. Because predictive analytics goes beyond sorting and describing data, it relies heavily on complex models designed to make inferences about the data it encounters. These models utilize algorithms and machine learning to analyze past and present data in order to provide future trends. For businesses who want to incorporate predictive analytics into their learning analytics strategy, the following steps should be considered:.

Here are a few key benefits that businesses can expect to find when incorporating predictive analytics into their overall learning analytics strategy:. Many businesses are beginning to incorporate predictive analytics into their learning analytics strategy by utilizing the predictive forecasting features offered in Learning Management Systems and specialized software. You can think of Predictive Analytics as then using this historical data to develop statistical models that will then forecast about future possibilities. This methodology is not only recommended for profit-based businesses, but the same principle can be applied to a non-profit company.

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Predictive analysis is very useful to profit organization, and nonprofit organizations can also benefit likewise. Using predictive analysis will help my organization to analyze historical and comparative data about their donors, and help them to predict a future behavior. Predictive analysis can also predict the likelihood of a donor to respond to direct mail solicitation, or to leave a bequest, and the probability of giving a principal gift.

Predictive analysis can synthesis data to make predictions, and can also offer option for the nonprofit to make most out of its predictions. On segmentation of donors; predictive analysis. Get Access.

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