Welcome back for Week 9 of Workout Wednesday, Power BI edition. If you’re joining us for the first time, welcome! You can jump right in this week, where we’ll be exploring our data in Power BI.
For this week’s challenge are going to use anomaly detection and forecasting to gain a deeper understanding of what’s going on now and in the future in the Great Lakes. For those of you participating in the Tableau challenge, you may remember doing something similar in Week 5.
This challenge may also look similar to the Power BI Week 7 challenge, as we’re building off of David’s report.
- Find a Power Query transformation that will change the individual lake columns into rows. You’ll end up with only three columns loaded into your data model (this comes straight from Week 7)
- Add a line chart that displays the average coverage by year, forecasted out to the year 2030.
- Add a second line chart that also displays average coverage by year showing anomalies at 75% sensitivity, explained by Lake.
- Formatting is totally up to you! We’ve been loving the creativity that the #WOW2021 community has been producing – keep it coming!
- Answer the following questions:
- What is the projected average ice coverage in 2030?
- Which lake contributed most to data anomalies?
You all made some beautiful reports in Week 7 using data on maximum ice coverage from NOAA’s Great Lakes Environmental Research Laboratory. If you participated in Week 7, use that report as a starter and we’ll build on it this week.
If you did not participate in Week 7, that’s okay! You can get the raw data from Data.World and use Power BI’s built-in Data.World connector, or alternatively get it in Excel format from GitHub. A lake can have ice coverage ranging from 0 (no ice) to 100 (frozen over).
If you’re only interested in visualizing data and not transforming it for this challenge, use this PBIX from GitHub (requires Power BI Desktop December 2020 or later).
After you finish your workout, share on Twitter using the hashtags #WOW2021 and #PowerBI, and tag @JSBaucke, @MMarie, @shan_gsd and @dataveld. Also make sure to fill out the Submission Tracker so that we can count you as a participant this week in order to track our participation throughout the year.