Analysing and visualing data.

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Review The Power of Good Design and select three of the ten principles noted for good design. Next in R, utilize these three principles in a problem that you will solve. First note the problem to solve, the dataset (where the information was pulled from), and what methods you are going to take to solve the problem. Ensure the problem is simple enough to complete within a two-page document. For example, I need to purchase a house and want to know what my options are given x amount of dollars and x location based on a sample of data from Zillow within each location.
Ensure there is data visualization in the homework and note how it relates to the three principles selected.
Link for the power of good design (https://www.vitsoe.com/gb/about/good-design)

Homework 2
( Business Intelligence(chapter 3 and 4))
Complete the following assignment in one MS Word document:

Chapter 3.
How do you describe the importance of data in analytics? Can we think of analytics without data? Explain.

Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum?

Where do the data for business analytics come from? What are the sources and the nature of those incoming data?

What are the most common metrics that make for ­analytics-ready data?

Go to data.gov—a U.S. government–sponsored data portal that has a very large number of data sets on a wide variety of topics ranging from healthcare to education, climate to public safety. Pick a topic that you are most passionate about. Go through the topic-­specific information and explanation provided on the site. Explore the possibilities of downloading the data, and use your favorite data visualization tool to create your own meaningful information and visualizations.

Chapter 4.
Define data mining. Why are there many names and definitions for data mining?

What are the main reasons for the recent popularity of data mining?

Discuss what an organization should consider before making a decision to purchase data mining software.

Distinguish data mining from other analytical tools and techniques.