MIS772 Predictive Analytics Assignment Help

MIS772 Predictive Analytics Assignment Help
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MIS772 Predictive Analytics Assignment Help Online

With MIS772, students gain hands-on experience with the predictive analytics software tools that are widely used globally. Students may find it difficult to understand this subject-matter as it involves a lot of practical aspects. So, when they are given assignments to compose on this topic, they avail MIS772 Predictive Analytics assignment help. Our online best AUS writers before composing the assignments do thorough research on the subject matter so you can be assured of receiving a top quality assignment writing help. Our tutors always submit the assignments before the deadline and you can be assured of receiving top grades.

Concept of MIS772 Predictive Analytics

Predictive Analytics is the use of statistical algorithms, data, and machine learning techniques for identifying future results based on historical data. The objective is to go far beyond what has happened and to give you the best assessment regarding what shall happen in the future.

MIS772 Predictive Analytics has workshops that have three sessions; MIT1-MIT3, and also MIT-4, if wished. By completing these workshops, students shall understand the way to use RapidMiner or RM to gain insights, explore data into a problem domain, make classification models, and predictions based on these models.

The workshop shall rely on the knowledge of students on the techniques and methods introduced in the classes. During the workshop including on-cloud and on-campus, students shall work individually.

Importance of Predictive Analytics

Organizations use Predictive Analytics for helping to solve problems and also to uncover new opportunities. Some of its common uses as stated in our MIS772 Predictive Analytics case study help are as follows:

  • Detecting fraud: Multiple analytics methods are able to improve pattern detection and also prevent criminal behavior. Cybersecurity is becoming a growing concern and behavioral analytics examine all kinds of actions in the real-time network to locate abnormalities, which indicate fraud, advanced constant threats, vulnerabilities.
  • Optimizing marketing campaigns: It is used for determining customer responses and promoting cross-sell opportunities. It help businesses retain, attract, and grow highly profitable customers.
  • Improving operations: Many companies use it for forecasting inventory as well as for managing resources. Airlines use it to set the ticket prices. Hotels use it for predicting the number of guests for increasing revenue and maximizing occupancy. It enables organizations in functioning very efficiently.
  • Reducing risk: Credit scores are used for assessing the likelihood of a buyer’s default in making purchases. This is a good example of the predictive analytics. In a credit score, a number is generated by predictive model that includes all data related to the creditworthiness of a person. Other uses include insurance collections and claims.

Who Uses Predictive Analytics?

The following sectors use Predictive Analytics. Our MIS772 Predictive Analytics assignment writing experts have explained them in detail.

Banking and Financial Services

The financial industry has a huge amount of data and money at stake and it has since a long time embraced predictive analytics for detecting and reducing fraud, measuring credit risk, maximizing up-sell and cross-sell opportunities, and for retaining valuable customers.


Retailers all over the places use predictive analytics for price optimization and merchandise planning, analyzing the effectiveness of a promotional event, and determining the offers that are appropriate for customers.

Oil and Gas

Whether it means predicting future resource needs or equipment failures, reducing reliability and safety risks, improving overall performance, the oil and gas industry has utilized predictive analytics.

Government and Public Sector

Government is a key player for the advancement of computer technologies. The government uses predictive analytics like other industries for improving the service and performance, detecting and preventing fraud, and understanding consumer behavior in a better way. They also use it to improve cybersecurity.

Health Insurance

Apart from detecting fraud claims, health insurance industries are taking steps for identifying patients who are at risk to develop chronic disease and find out the interventions that are the best.


It is important for the manufacturers to locate factors that lead to reduced production and quality failures along with optimizing parts, distribution, and service resources.

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