You are a real estate and property management business analyst in a big city. Your companys leadership team supports building reasonably priced housing in areas that have well-performing schools with low school dropout rates (home price and dropout rate are the key factors). You wish to commission a consulting team of business and data analysts to build a full dashboard that will address the best locations for new construction projects within the five boroughs of the city based on the companys mission and various performance metrics.
You decide to build a basic prototype model of the dashboard using the home price and dropout rate data for one borough. This prototype model will help you explain the project to your company’s leadership before you meet with the consultants who will build the full dashboard with many other predictive factors. You also want to be able to clearly report a data story about the project to the leadership team using your prototype.
To ensure you understand the data that will be included in the dashboard model, you will first need to connect your Excel data with Tableau and look at it visually.
Use the provided D466 Task 1 Data Set to complete this task.
Provided model data for the borough:
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A. Describe the two main factorshome price and dropout ratein the scenario.
1. Explain, using data from the D466 Task 1 Data Set, the current state of home prices.
a. Use Tableau to create an appropriate data visualization that shows the current state of home prices.
b. Identify one design technique you used in the visualization from part A1a and explain how it addresses a common accessibility issue.
c. Identify one design technique different than the one identified in part A1b and explain how it contributes to effective representation of the information in the data set.
2. Explain, using data from the D466 Task 1 Data Set, how a change in school dropout rates would affect home prices.
a. Use Tableau to create an appropriate data visualization that shows how a change in school dropout rates (independent variable) would affect home prices (dependent variable).
b. Identify one design technique you used in the visualization from part A2a and explain how it addresses a common accessibility issue.
c. Identify one different design technique than the one used in part A2b and explain how it contributes to effective representation of the information in the data set.