[MUSIC] Welcome back. In the last few modules, you have written your project proposal using a design checklist. You've prepped and imported your data into Tableau. You've conducted exploratory analysis for your data and created a dashboard that includes KPIs. In this milestone, you'll begin to create your data stories. You'll outline the basic arch of your story, or draft a narrative description of what you data visualization will communicate. You began that process in a previous milestone, but now you will start assembling your story using Tableau. If you're creating a single frame visualization, consider what will be the most important elements to frame and how you will prioritize the space you have to work with. As Minaj showed us, a whole story can be told in a single frame vis. You all need to determine what would be the best combination of narrative, framing, and level of sophistication to meet the needs of your defined audience. If you're creating a multi-frame data story, remember from the last course, that a story is something that has three core connected elements, the three C's; context, challenge and a conclusion. This will be a useful framework through which to consider your narrative structure, but there certainly others as well. Now, you will use story points to assemble your data using as many points as necessary to communicate the full story. Make sure you're capturing each point and sequencing them in the correct order. Throughout the specialization, you've seen that stories can be an incredibly powerful tool for several reasons. There's some evidence for example, that stories can help people's comprehension and recall. They can provide important context and in certain instances, even faster empathy and emotional connection to the findings. Of course, like any powerful tool, there are potential pros and cons to using stories. I've already mentioned a few pros. The cons include distorting the data by terming meaningless patterns into false narratives. That is the same potential stories in a pattern of data that leads to false interpretations and conclusions. I encourage you to keep these pros and cons in mind when drafting your narrative. And to strive to make your data stories as true to the data as possible. At this stage, please, focus on what your visualization communicates as opposed to how it looks. You'll make your final design decisions in the last milestone. When you're ready, you upload a link to your data story for peer review. Okay. Let's get to it.