Data science is used these days in all industries, whether it is IT, Healthcare, Insurance, Finance, Entertainment, or Media.

Association rule and recommendation engine case study

This case study will help you in understanding the association rule, recommendation engine, data analytics tools such as Hadoop, Spark and how to leverage these tools for the business growth. For example, Netflix, the largest internet-television network used big data analytics to understand the users’ needs and by focusing on their requirements, increased the customers base. Its reality TV shows work on the recommendation approach, which also brings in customer’s loyalty. This is a perfect example for the business that demands constant engagement and association of users for its growth and success.

Reverse engineering case study

In this case study, you will learn predictive modelling and reverse engineering. The Mint.com website is one such example, which provides free insights of where money goes to for its investors. It grew from zero to 100, 000 members in just six months. It followed the reverse engineering marketing methodology to gain the faith in the product and started working on the solution to way back to the individual data.

Statistical models case study

This case study focuses on big data analytics and parallels statistical models. Pharmaceutical industries get the advantage of such tools to prioritize the products for the treatment. The parallel statistical model helps in forecasting the likelihood of doctors prescribing medicine and henceforth, demand for that product. You will prepare a real-time model of how these tools can be helpful for clinical research scientists to formulae medicine.

Predictive analytics and decision tree case study

You will learn how to use predictive analytics and decision tree in this case study. You can use these tools for the education industry to forecast the dropout rates of students based upon their performance. For example, the University of Florida uses IBM Cognos Analytics to focus on the student's performance vs dropout ratio. Accordingly, it provides solutions to retain students.