Alteryx Academy

  Hello Community Members,   A solution to last week’s challenge can be found here.    This challenge was submitted by Griffin Welsh @griffinwelsh. Thank you, Griffin, for this great challenge! Job hunting today takes a lot of time and effort. You are not only sifting through hundreds of job postings but also crafting tailored resumes, writing cover letters, following up with recruiters, and networking to land the perfect role. Once the offers start coming in, how do you decide which job is truly the best? Your challenge is to compare multiple job offers based on the costs you will have to commute to work. You have two datasets: Job Details Text Input: Job details from six companies you received offers from. Constants Text Input: Information about fuel prices, car maintenance costs, miles per gallon, and your home location.   Your tasks are the following:   Calculate your annual fuel cost and vehicle maintenance cost for each job. Consider the following for this calculation: Travel time to office Daily fuel cost Vehicle maintenance cost How many days you will be in the office   Calculate your annual travel time (coming to and from work).   Need a refresher? Review the following lessons in Academy to gear up: Diving Into Expressions Creating Spatial Objects   Good luck! The Academy Team   Download Start File   Download Solution File ... View more

Happy New Year, Community Members!   A big thank you to Erin Miller (@Erin)  for this special submission. Erin, you've contributed so many fantastic challenges throughout 2025, and it’s only fitting that Challenge #500 comes from you. We truly appreciate your creativity and dedication. Thank you again!   A solution to last week’s challenge can be found here.   It’s 2026: time for resolutions, fresh routines, and rethinking your media diet.   Your friend has been deep into true crime podcasts, so deep, in fact, that their spouse is starting to give them some serious side-eye. It’s clearly time for a change: something lighter, brighter, or just totally different.   Luckily, you’ve come across a daily dataset of Spotify’s Top 200 Podcast Episodes, complete with detailed show and episode info from the Spotify API. What better way to kick off the new year than with a chained analytic app to help your friend discover their next podcast obsession?   Your 2026 Podcast Discovery App – Let’s Build It!   Create a chained app experience where each selection refines the next. The app should include the following filters:   App 1 – Filter by Region App 2 – Filter by Language (Feeling a little extra? Let the user select multiple languages!) App 3 – Filter by Average Podcast Duration (Really feeling extra? Group durations into 15-minute intervals for a smooth user experience!)   After all filters have been applied, calculate the average show rank and identify the top-ranked episode for each show. The final result should include a summary of the selected filters and a table displaying the top 10 shows by average rank, along with the show description, average show duration, publisher, highest-ranked episode, and episode description.   Did you know that Alteryx has a podcast within the Alteryx Community? Check out the Alter Everything Podcast here: https://community.alteryx.com/t5/Alter-Everything-Podcast/Alter-Everything-Podcast-Episode-Guide/ba-p/450065    Once you have completed your challenge, include your solution file and a screenshot of your workflow as attachments to your comment.   Good Luck! The Academy Team   Source: https://www.kaggle.com/datasets/daniilmiheev/top-spotify-podcasts-daily-updated    Download Start File ... View more

    Hi Community members,   A solution to last week’s challenge can be found here.    This challenge was submitted by Casey Koopmans @cwkoops. Thank you, Casey, for this interesting challenge!   In global supply chain operations, duty drawback programs allow exporters to reclaim duties paid on imported raw materials once the resulting finished goods are exported. To comply with such programs, companies must maintain traceability between the raw materials used and the finished goods produced. For this challenge, imagine you work with a manufacturer that processes raw materials into finished goods. Each raw material is received in lots, and the manufacturer needs to trace how much of each raw material lot is consumed in each finished good lot, following a strict First In, First Out (FIFO) usage policy. Your task is to develop a FIFO allocation model that maps the consumption of raw material lots to finished good lots, enabling full traceability. You are provided with two datasets: a.        Raw Material Lots: a table that lists all the raw material lots received: b.        Finished Good Requirements: a table that lists each finished good lot and its corresponding raw material requirements:   Each finished good lot consumes a certain amount of a specific raw material type (SUB), which must be traced back to specific raw material lots.   Your task for this challenge: Using FIFO allocation, build an iterative macro that helps determine which raw material lots are consumed by each finished good lot, and how much of each lot is used. To do so, consider the following:   Group raw material lots by ITEM (raw material type) and sort them in the order received. Iterate through each finished good lot in the order produced. For each finished good lot:    - Identify the required SUB (raw material type) and SUB QTY (quantity required).    - Allocate this quantity using the earliest available raw material lots (FIFO).    - Deduct the used quantity from raw lot availability and record which lots were used and how much. Output a table that shows:    - Finished Good Lot ID (FG LOT)    - Raw Material Type (SUB)    - Raw Material Lot (RAW LOT)    - Quantity Used (QTY USED)   Source: Sample Data set provided in the workflow as text inputs.   Good luck! The Academy Team   Download Start File   Download Solution File ... View more

A solution to last week's challenge can be found here!    This challenge was created for a HackCU hackathon event in which teams were formed and were given 24 consecutive hours and Alteryx Designer to solve the challenge.   In this challenge you must break apart the given [encoded_string] into two character pairs and then build a decoder table, mapping the two-character pairs into ASCII characters to reveal a pig-latin encoded document.   To solve, or not to solve: that is the question.   ... View more

A solution to last week's challenge can be found here.    This week's challenge was submitted by @AShapiro  - Thanks for your contribution!   What’s your favorite flavor of ice cream? Hard to choose just one? With ranked choice voting (RCV), you don’t have to! With RCV, you can rank your favorites in order of choice. For this week’s challenge, we have the results of a Favorite Flavors of Ice Cream poll. Build a workflow to conduct a RCV to find the voters’ favorite flavor and the total number of voting rounds. If a flavor receives more than half of the first choices, that flavor wins. If not, the flavor with the fewest first choice votes is eliminated. For voters who picked that flavor as their “Number 1”, their votes shift to their next choice. The process continues until a flavor has more than half the votes. Click here for a video explanation of RCV. ... View more