Alteryx Academy

Hi Maveryx,   We posted the solution JSON file to Cloud Quest #12. Check it out and let us know what you think! Send suggestions to academy@alteryx.com or leave a comment below!     Let’s dive into this week's quest!   Download and extract the provided JSON file containing your starting data and workflow files. Upload the provided Cloud Quest 13 - Start File.json file into your Analytics Cloud library. All necessary datasets are contained within Text Input tools in the workflow.   For more detailed instructions on how to import and export Designer Cloud workflow files, check out the pinned article Cloud Quest Submission Process Update.     Scenario:   You are a big fan of Formula 1, and you want to run some simple statistics.   Your input data contains information about teams and their drivers from 2019 to 2021. Using this dataset, answer the following questions:   What is the average age of all drivers in the field? Calculate the number podiums each team accumulated in 2019, 2020, and 2021. Which team accumulated the most total podiums, and how many did they accumulate? Which team had the biggest point differential between their best and worst drivers in 2021? Which country produced the most drivers, and how many drivers are from that country? (According to their Place of Birth)   Hint: Did you know you can create new columns based on a summarize function within one Cross Tab tool?   A combination of the Summarize, Cross Tab, Sample, and Formula tools should solve your problem, but not necessarily in this sequence. If you find yourself struggling with any of the tasks, feel free to explore these interactive lessons in the Maveryx Academy for guidance: Getting Started with Designer Cloud Building Connections in Designer Cloud Building Your Workflow in Designer Cloud   Once you have completed your quest, go back to your Analytics Cloud library. Download your workflow solution file. Include your JSON file and a screenshot of your workflow as attachments to your comment.   Here’s to a successful quest!     ... View more

  Hi Community members,   A solution to last week’s challenge can be found here.    This week's challenge was inspired by a submission from Vikas Gupta. We appreciate Vikas' contribution! It is great to include the versatile RegEx tool in our repository of challenges.   As we celebrated Mother’s Day last week, why not embark on a unique challenge? Use your regular expression skills to clean up a line of a poem that you can write on a card and present to your mom, accompanied by a bouquet of roses.     Your dataset contains a list of lines from poems mixed with the dates they were written.   Your tasks: Remove the dates from the poems and replace each date with a comma. Create a new column that contains the dates formatted in Alteryx date format.   Bonus: If you have the Text Mining palette installed, create a word cloud to discover which words stood out.   Need a refresher? Review these lessons in Academy to gear up: Creating Regular Expressions Using RegEx in Expressions Parsing Data with RegEx   Good luck, and happy Mother’s Day!   The Academy Team   Download Start File   Download Solution File ... View more

  Hi Community members,   A solution to last week’s challenge can be found here.   This two-part challenge was submitted by Guilherme Dias, @3I_ATLAS. Thank you, Guilherme, for your great submission!   Electric vehicle (EV) production data offers powerful insights into innovation, market trends, and manufacturer behavior. As researchers dig into the data, your task is to help uncover major production shifts and unique behaviors in EV model lifecycles. For part 1 of this challenge, your analysis should only include data from 2010 to 2024. Exclude data from the year 2025, as it contains only partial records. Here are the three tasks you need to accomplish:   Identify the year with the largest increase and the largest decrease in total EV production compared to its previous year. Find the top 3 EV models that had the longest production pause (in years) before resuming production again. Only consider models that had a production gap followed by a confirmed comeback. In the most recent full year of data, determine which manufacturer introduced the most units of never-before-seen models. Ensure that your logic dynamically adjusts to the latest year, without hardcoded values. You are provided with one dataset: Electric Vehicle Data – provides the model year, manufacturer (brand) and car model.   Once you have completed your challenge, include your solution file and a screenshot of your workflow as attachments to your comment.   Stay tuned for part two of this challenge! Good Luck! The Academy Team   Source: https://catalog.data.gov/dataset/electric-vehicle-population-data   Download Start File   Download Solution File ... View more

Hi Community members,   A solution to last week’s challenge can be found here.   This two-part challenge was submitted by Guilherme Dias, @3I_ATLAS. Thank you, Guilherme, for your great submission!   In the previous challenge, you have already identified critical production trends and model behaviors for electric vehicles. Now, shift your focus to innovation and decline — two sides of product lifecycle in the EV industry.   In the second part of this challenge, you analyze which years saw surges of new model launches and which saw waves of production extinction. Reminder: Only include years from 2010 to 2024 in your analysis, as 2025 data is incomplete.   Here are the two tasks you need to accomplish:   Determine which two years had the most distinct new models launched and from which brands were these models launched. Identify the year with the highest number of distinct models that stopped being produced, relative to the prior year. Count each model that was produced in year Y but not in year Y+1 as “extinct,” even if it returns in later years.   You are provided with one dataset (the same dataset from part 1 of this challenge): Electric Vehicle Data – provides the model year, manufacturer (brand) and car model.   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://catalog.data.gov/dataset/electric-vehicle-population-data   Download Start File   Download Solution File ... View more

Hi Community members,   A solution to last week’s challenge can be found here.   This challenge was submitted by our ACE Carolyn Canterman (@Carolyn). Thank you, Carolyn for your submission!   The Sarbanes-Oxley Act of 2002 (SOX) is a U.S. federal law enacted to protect investors by improving the accuracy and reliability of corporate disclosures. Under SOX, companies must implement internal controls over financial reporting.   These controls are categorized as: Key Controls – considered critical for financial reporting and subject to stricter review Non-Key Controls – important, but with less scrutiny   Each SOX control requires: A Preparer, who performs the analysis. A Reviewer, who independently reviews the work.   Both the Preparer and Reviewer must sign off by entering their name and date. This sign-off process is logged as evidence of proper control execution.   You are an auditor reviewing the SOX Control Sign-Off Log for accuracy and compliance.   You will be provided with three input files: The SOX Control Sign Off Log, evidencing the Preparer and Reviewer sign off for each Control, for two different months. Information on the employees. List of issues that you are checking for.   Use the Issue Rule List to validate each Control entry. A control has an issue if it violates any of the following rules: Both Preparer and Reviewer must be present, and they must be different individuals. Sign-off dates must follow proper sequence: Both Preparer and Reviewer must have a date. Reviewer date must be within 5 days after the Preparer date (inclusive). Reviewer date cannot be before the Preparer date. If the SOX Control is marked as a Key Control, the Reviewer must be a manager.   Your Tasks   Task 1: For each Control in each Period, count how many issues are present according to the rules above. Note: If information is missing or unclear and you cannot determine whether there’s an issue, do not count it as an issue.   Task 2: Which Period had more total issues — March 2025 or April 2025?   Task 3: Task 3: Across both periods, which control had the most issues in total?   Bonus Task: Which person is associated with the most total issues across all controls and periods?   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   Download Start File Download Solution File ... View more