Write 5-7 sentences (100-140 words) about data sources discussed during your real-life data conversation.First, consider your data conversation and how it went. Here are some questions to help you get started:Was there anything challenging about getting the conversation started?Were there questions you didn’t get to ask? Did you manage your time effectively?Did you take notes? Are they as detailed as you need them to be?Are you missing any information? Is there anything that you still find unclear or vague?  If you could do the conversation over again, is there anything you would change?Next, turn your attention to your notes and reflect on what you know about the data itself:What are the sources of data available for the project?Which data sources were qualitative and which were quantitative? Explain your answer. What decisions could you make when considering each data source separately? Could you make different decisions about the data if you combined it? If so, give an example.Is there any kind of data that isn’t available, but you would like to find? If so, what is it, and why would you like to know more about it?

Before you begin your conversation about data, consider each of the above steps. Think about potential candidates, brainstorm some SMART questions, and get an idea of the information you want to record during your conversation. Then, reflect on your conversation:What SMART questions did you ask? How did these questions tie into the field of the person you chatted with? What insights did you discover during your conversation? How did the SMART framework help you arrive at your conclusions?

write 2-3 sentences (40-60 words) in response to each of the following questions:Using all of the information you learned while exploring in Kaggle, how would you thoroughly describe these datasets to someone else?How do you think sharing interactive notebooks online can help you develop your data analysis skills?

Consider the following questions:What do you think will be the easiest and most difficult parts of analyzing data? What are you most excited to learn how to do?How has what you’ve learned so far prepared you for learning about analyzing data?Submit two or more paragraphs (100-150 words) to respond to these questions

Consider what you have learned about data insufficiency and the steps for how to avoid it:Why are pre-cleaning steps important to complete prior to data cleaning?What problems might occur if you don't follow these steps? Now, write 2-3 sentences (40-60 words) in response to each of these questions. Type your response in the text box below.

write 2-3 sentences (40-60 words) in response to each of the following questions:What did linking data from multiple sources allow you to do with your visualization in Tableau? What other kinds of datasets could you link to the four you used in this activity? What kinds of comparisons or insights could you make?If you couldn’t link data in this way, how would you make complex comparative datasets and visualizations like this?