the Wireframe for your Dashboard. Explain the persona of your stakeholder, give a brief explanation on why you chose the specific relationships in your Wireframe, and what the overall story is for your Dashboard.

Overview:

The Student Loans dataset was obtained from Enterprise Data Warehouse and published on September 30, 2020. This dataset contains demographic and financial information regarding federal student loan debt in the United States.

Involved Fields:

• Year: The timeframe for debt.
• Quarter: The period of the year for debt.
• Amount: The range of loans one can borrow.
• Amount Borrowed (in millions): The amount of student loans individuals borrowed.
• Dollars Outstanding (in millions): The amount of debt needed to be collected.
• Location: States in the U.S. that have debts and federal student loans.
• Age: The age ranges for debt holders.
• Number of Borrowers (in thousands): The number of people who borrowed money for student loans.
• Balance (in billions): The total amount of debt for each state.

Part 2:

1. Age and Debt:

The correlation between an individual's age and the amount of debt will be looked into. It begs the following questions: does age affect the amount of debt borrowed/outstanding and what age group has the highest/lowest debt balance? This is significant as it will display how the amount of debt has altered over time with various generations.

1. Location and Debt:

The dataset contains information about the number of borrowers and the total amount borrowed that can be found in each state. While education is salient, it can also be quite expensive. It will be interesting to learn if there is a difference in the total amount of debt from one state to another. We can also consider the loans as subsidized or unsubsidized. Is interest really adding to their debt, and is it only one state that has different levels of debt or are there multiple? It will be intriguing to research how the amount of debt may vary depending on location.

1. Year and Debt:

This relationship will track the changes in debt throughout the time period of the dataset. In this dataset, the time range is from 2017 to 2020. With increasing college prices and a volatile economy, student loan borrowing and repayment can vary from year to year. The importance of this is that the past, present, and future trends in student loans, as well as how much debt America is in, will be examined. Another stimulating aspect of this relationship is the possible political ramifications, as forgiving student loans continues to be a much-discussed topic in the federal government.

The goal of this assignment is to get your team a good foundation before you actually start building your dashboard in your Business Intelligence tool. A Wireframe is similar to an outline for a research paper, and is something you should do before you start putting your dashboard together. A Wireframe is simply a written draft of your two dashboard pages. In it you will sketch out each of the figures you are initially thinking of using, and denote what relationships will be shown in the given figures.

Because building a dashboard is both an analytical process, as well as a creative process, it is crucial you have your ideas generally fleshed out in advance. A solid Wireframe will minimize frustration for your team, and make the dashboard construction process much more efficient. At this stage you should establish the stakeholder persona you are building the dashboard for, as their perspective/motivations are important things to consider through the design process.

For your Wireframe submission you should start off with a brief explanation on what your stakeholder persona is. Your Wireframe should then have an image for each dashboard page (you can take pictures of the sketches and insert them into a Word document). Then you need to have a brief explanation of what each figure is trying to show/convey. Finally, give a brief explanation of what you are planning the overall story of your dashboard to be.

B D E F G H K L M N O P Q R S T Amount Borrowed Dollars Outstanding Year Quarter Amount (in millions) (in millions) 2017 04 0-5k $16.9 $6,100 2017 04 5k-10k $45.6 $6,200 2017 Q4 10k-20k $110.7 $7, 70 VO U A W N 2017 04 20k-40k $220.6 $7,800 2017 04 40k-60k $154.6 $3,200 2017 04 60k-80k $110.5 $1,600 2017 Q4 80k-100k $71.3 $80 2017 Q4 100k-200k $191.7 $1,400 10 2017 04 200k+ $133.5 $500 11 2018 Q1 0-5k $17.7 $6,400 12 2018 Q1 5k-10k $45.5 $6,200 13 2018 Q1 10k-20k $110.8 $7, 700 14 2018 01 20k-40k $220.2 $7,800 15 2018 Q1 40k-60k $155.7 $3,200 16 2018 60k-80k $1 12.6 $1,600 17 2018 Q1 80k-100k $72.8 $800 18 2018 Q1 100k-200k $195.5 $1,400 19 2018 Q1 200k+ $139.0 $50 20 2018 Q2 0-5k $15.5 $5,600 21 2018 Q2 5k-10k $45.7 $6,400 22 2018 Q2 10k-20k $114.1 $7,900 23 2018 Q2 20k-40k $224.3 $7,900 24 2018 Q2 40k-60k $159.7 $3,300 25 2018 Q2 60k-80k $117.6 $1,700 26 2018 Q2 80k-100k $76.0 $90 27 2018 Q2 100k-200k $204.2 $1,500 28 2018 Q2 200k+ $147.7 $500 29 2018 Q3 0-5k $15.3 $5,500 Portfolio by Debt Portfolio by Age Portfolio by Location and Age Portfolio by Location and Debt Portfolio by Location + Ready +A B D E F G H K L M N O P Q R S Amount Borrowed (in Year Dollars Outstanding Quarter Age millions) (in millions) 2017 Q2 24 and younger $134.3 $8,600 W N 2017 Q2 25-34 $477.4 $15,300 2017 Q2 35-49 $484.7 $13,500 2017 Q2 50-61 $191.9 $5,600 2017 Q2 62 and Older $51.9 $1,700 2017 03 24 and younger $126.5 $8,200 2017 Q3 25-34 $477.8 $15,200 2017 Q3 35-49 $490.2 $13,500 10 2017 Q3 50-61 $194.1 $5,600 11 2017 Q3 62 and Older $53.2 $1,700 12 2017 Q4 24 and younger $130.3 $8, 700 13 2017 Q4 25-34 $484.0 $15,300 14 2017 04 35-49 $502.2 $13,700 15 2017 Q4 50-61 $199.8 $5,700 16 2017 Q4 62 and Older $55.4 $1,700 17 2018 Q1 24 and younger $124.4 $8,600 18 2018 Q1 25-34 $483.8 $15,300 19 2018 Q1 35-49 $511.3 $13,800 20 2018 Q1 50-61 $204.0 $5,700 21 2018 Q1 62 and Older $57.9 $1,800 22 2018 Q2 24 and younger $129.1 $8,400 23 2018 Q2 25-34 $488.6 $15,200 24 2018 Q2 35-49 $522.4 $13,800 25 2018 Q2 50-61 $210.3 $5,800 26 2018 Q2 62 and Older $60.5 $1,800 27 2018 Q3 24 and younger $121.6 $8,000 28 2018 Q3 25-34 $489.0 $15,100 29 2018 Q3 35-49 $529.6 $13,800 Portfolio by Debt Portfolio by Age Portfolio by Location and Age Portfolio by Location and Debt Portfolio by Location + Ready + 100%A1 X V fx Location A B C D E F G H J K L M N O P Q R S Dollars Number of Location Age Outstanding (in Borrowers (in millions) thousands) Alabama 24 or Younger $1,740 117.2 Alabama 25-34 $7,070 202.6 Alabama 35-49 $9,310 189.0 Alabama 50-61 $3,550 80.1 Alabama 62 and Older $96 24.4 Alaska 24 or Younger $110 9.7 Alaska 25-34 $740 24.8 Alaska 35-49 $930 21.3 Alaska 50-61 $360 8.2 11 Alaska 62 and Older $110 2.5 12 Arizona 24 or Younger $1,680 128.1 13 Arizona 25-34 $9,410 294.9 14 Arizona 35-49 $12,270 273.5 15 Arizona 50-61 $5,050 1 19.8 16 Arizona 62 and Older $1,620 39.2 17 Arkansas 24 or Younger $97 72.0 18 Arkansas 25-34 $4,030 128.9 19 Arkansas 35-49 $5,220 118.0 20 Arkansas 50-61 $1,820 45.4 21 Arkansas 62 and Older $490 12.9 22 California 24 or Younger $8,960 646.9 23 California 25-34 $50,090 1,452.4 24 California 35-49 $50,870 1,061.7 25 California 50-61 $22,280 504.4 26 California 62 and Older $7,890 185.5 27 Colorado 24 or Younger $1,670 123.1 Portfolio by Debt Portfolio by Age Portfolio by Location and Age Portfolio by Location and Debt Portfolio by Location + Ready + 100%C1 X V fx 'Dollars Outstanding (in millions) A B C D E F G H K L M N O P Q R S Dollars Number of Location Amount Outstanding (in Borrowers (in millions) thousands) 2 Alabama