Case Summary: Let's see how we might perform some simple Data Analytics. The purpose of this lab is to help you identify relevant questions that may be answered using Data Analytics. You were just hired as an analyst for a credit rating agency that evaluates publicly listed companies in the United States. The agency already has some Data Analytics tools that it uses to evaluate financial statements and determine which companies have higher risk and which companies are growing quickly. The agency uses these analytics to provide ratings that will allow lenders to set interest rates and determine whether to lend money in the first place. As a new analyst, you're determined to make a good first impression. Note: Submit your answers for the following Analysis Questions in the text entry field below. AQ1. Use what you know about financial statement analysis (or search the web if you need a refresher) to generate three different metrics for evaluating financial performance. For example, if you wanted to evaluate a company's profit margin from one year to the next your question might be, "Has Apple Inc's gross margin increased in the last 3 years?" AQ2. Next to each question generate a hypothetical answer to the question to help you identify what your expected output would be. You may use some insight or intuition or search for industry averages to inform your hypothesis. For example: "Hypothesis: Apple Inc's gross margin has increased slightly in the past 3 years." AQ3. Evaluate each question from Part 1. There are specific data attributes that will help you find the answer you're looking for. For example, if your question was "Has [Company X's] gross margin increased in the last 3 years?" and the expected answer is "Apple Inc's gross margin has increased slightly in the past 3 years," this tells you what attributes (or fields) to look for: company name, gross margin (sales revenues cost of goods sold), year