Course project overview - Power BI Tutorial

- [Instructor] Let's say that we work at a travel agency that offers California travel packages. In addition to our marketing, let's also say that we want to help them figure out an optimal time to visit Southern California by analyzing weather trends. Weather data sets are a great way to explore data methods for tools like Power BI. It's relevant to almost everyone, consistent over time and frequently updated. The variety and diversity of weather data and their formats also provide great examples for the techniques that we'll learn in this course. We can get free publicly available weather data from a number of different online resources. One of them is the National Weather Service or NWS through the website weather.gov. Another weather data resource is NOAA, which offers a portal called Climate Data Online for querying data sets. In the exercise files for this course, I'm going to use daily weather data flat files that I obtained through this CDO portal. This weather data will include the latest measurements as of the course recording date. However, if you'd like to obtain the latest data to use on your own, here's how you can query the latest data set. We'll first choose the search tool from our CDO homepage. We'll then input the parameters that we want to query the weather data set with. In the first dropdown menu list for the type of data set, let's select daily summaries. By default, the select date range will display the latest dates in which we have data. We can always change this later if we would like. The dropdown menu for the search for options then defaults to stations. Let's leave this as is for now as well. And the search term text box, let's search for the Santa Barbara California airport. We'll then search for this airport location. Airports are a great places to get weather data from because air traffic controllers rely on accurate and consistent measurements to make critical flight decisions. We see that the search results display the most likely match the top, but also other potential stations to use as well. If we want more information on the geographical locations of these stations, we can take a closer look at them on the map. If we click on the hyperlink to view full details for the Santa Barbara Municipal Airport, we can see the metadata for that station. This includes the date range of available daily data points that go back to 1941 and the percentage of data coverage over this time period. We can also note the station ID for this location to use later in other data query methods. Once we confirm this selected station, let's add it to our cart. We'll then click on the cart list in the top right to specify how we want to receive our data results. For the output format of our data, let's select the PDF radio button and the checkbox next to include documentation. Let's change the date range to the dates between the 1st of January, 2023 and the 31st of December in the same year. We'll then apply the this date range. It's important to note that we can't query more than one calendar year at a time, so we'll need to query the data again to expand the date range to other years. We'll then click on the continue button at the bottom of the page. Lastly, we can confirm our data request and enter our email address where we'll receive the links to our data once the CDO portal runs our request. We can also obtain data in other format types like A CSV. This request type involves a few more steps though, so let's choose edit order to go back to the previous page. We'll change our format output type to CSV instead of PDF, and then click on the continue button again. There's now another page specific for the CSV format that involves choosing the fields to include. Let's select all the check boxes on the screen, then click on the continue button. Regardless of the selected format output type, we'll ultimately end up at the same final order page. Once we review our requested data and our destination email address, we'll click on the submit order button to run our data query. I ran the data request for Santa Barbara as both a PDF and CSV format for the year 2023, but to save the tedious of walking through both of them individually, I wanted to edit the order to show you how to do both in the same way that I did behind the scenes. I also obtained CSV weather data for the same location for all the available dates in 2024 and 2022. Also, you may not have your files in the same place that I do, so if you're looking to follow along, make sure you're pointing to the right directory in Power BI. You can do this by opening the source step and updating your file path to the location where you saved it on your computer. So for instance, my exercise files are located in the desktop folder and the sub folder exercise files. You'll want to update this file path to the one you're using on your own computer. And a little bit of a disclaimer, if you've ever used Power BI, you probably know that it's a constantly changing tool and yours might look a bit different, but the overall concepts and framework will be the same.