4 questions on baton rouge real estate price prediction using graphs

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Module 1 Assignment

In this first assignment, you will apply what you learned about big data analytics to a business problem, As an example, you are provided an Excel worksheet with real estate data for Baton Rouge. The data were downloaded from the redfin website in 2018. This assignment is to concentrate on the first and second step of the CRISP-DM cycle. Although CRISP-DM was proposed for data mining, we will adopt for this course because it serves as a good process when dealing with data analysis in general.

The general business problem we want to address is that of predicting price of a real estate property. For instance, suppose you work for Zillow and want to develop an algorithm for predicting price of a property.

Assignment 1 Instructions
  • Business Understanding: What is the specific business problem? Without looking at the data what variables should one collect predict price of a property? What does real estate research show what determines price? (Google)
  • Data understanding: Here you describe the data issues.
  • Analysis: here you describe the actions taken to prepare the data.
  • Conclusion: Here you summarize the main issues.


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