In this assignment, you’ve been tasked with exploring the U.S. government’s open data repository and selecting three datasets (https://catalog.data.gov/dataset).
For each dataset you choose, you will create a simple report (three distinct reports) in which you outline the contents of the data, the key fields contained therein, a set of 15 well-articulated exploratory questions one might ask of the dataset, and sample visualizations that aim to answer 2 of your questions. To help you in this process, you’ll be given a starter report template with each of the elements you will need to complete.
As you begin the exercise, consider the following parameters:
You must select three datasets.
Each selected dataset must include at least 150 data points (rows) and at least 5 fields (columns).
Your datasets should include a CSV or XLSX format.
Each dataset should be from a different sector and/or agency (i.e. Defense, Education, Agriculture).
Your data questions should each be structured in a format that can be “answered” using a data visualization that extracts a relationship, trend, pattern, or unusual observation. (See the Considerations and Helpful hints sections for sample questions.)
Each of your questions should be answerable primarily (or exclusively) using the dataset you’ve selected (i.e. your questions should not require you to aggregate data not readily in your possession).
For each question, offer your perspective on a hypothesized answer as well as a statement on why the question might matter to a government body. (See the Considerations and Helpful hints sections for sample questions.)
Include as a caption to your visualization a reference to the question it aims to answer.
As a final deliverable, you should upload each of your three report files as distinct documents. ( I will upload to my school)
Considerations and Helpful Hints
Review the rubric to see how this assignment will be graded.
This assignment is intended to challenge you in creating quality exploratory questions at volume and for disparate datasets. Over time, you will find yourself getting faster at generating and structuring such questions.
Consider the following as examples of quality exploratory questions:
To what extent does crop production seasonality differ year over year?
Which regions of the country do insurance providers pay the highest rates in medical expenditures?
To what extent do men and women experience disparities in receiving funding for small business grants?
For each of the above questions, one might offer the following hypotheses:
Crop production seasonality is relatively constant year over year.
Locations traditionally known to have high costs of living see higher rates of medical expenditures than other parts of the country.
Men and women experience relatively similar levels of funding for small business grants per application, but there exist many more male applicants than female.
For each of the above questions, the value might look like the following:
If seasonality is constant, government agencies can better coordinate aid packages to agricultural workers based on times of strongest need.
If medical bills are highest in sporadic locations — with no relationship to cost of living, there may be a need to increase regulation to prevent price gouging.
If women are less likely to pursue small business applications, government agencies may need to create special incentives to increase applications from female business owners.
Note that government data can be notoriously difficult to interpret. Spend the time necessary exploring the metadata associated with each dataset you select to ensure you understand what each column contains.
The word template for the 3 distinct reports are included FYI.
This assignment is a mix of Data Analytics and Business management
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