Cloud Quests
Elevate your workflow skills by solving real-world challenges using the Alteryx Analytics Cloud Platform.
Hi Maveryx,
Thanks for submitting your solutions for our first official Cloud Quest! In the video solution we posted, Alteryx Chief Evangelist, Joshua Burkhow (@joshuaburkhow) will guide you through the workflow (scroll down the page to locate the video).
Thank you, Josh, for the exceptional guidance!
For this week’s quest, you are taking on the role of a restaurant manager. You want to review customer purchase behavior to decide whether your restaurant should offer a meal deal that would add a side and drink to a pizza or burger purchase. To make this decision, you need to study recent transactions to determine the potential impact it could have.
The Point of Sale dataset includes the ticket-level information, and the two lookup tables categorize items into higher-level food types.
Your task is to determine the percentage of orders since July 1, 2013, that include the Food category (Pizza or Burger) paired with a Side AND Drink. To accomplish this, you need to determine the total number of orders placed within the specified timeframe and identify those that meet the criteria for the potential meal deal you are considering for your menu.
Hint 1: Remember to combine the dataset with the lookup tables and filter by date.
Hint 2: Remember to account for dates after June 30, 2013 to include July 1, 2013 in the output.
Your final result should look like the following image:
If you find yourself struggling with any of the tasks, feel free to explore these interactive lessons in Maveryx Academy for guidance:
- Getting Started with Designer Cloud
- Building Connections in Designer Cloud
- Building Your Workflow in Designer Cloud
Once you have completed this quest, capture a screenshot of your finalized workflow in Designer Cloud and attach the image of your solution to a comment on this post.
Here’s to a successful quest!
SOLUTION
We want to hear from you!
As we introduce our Cloud Quests for the first time, we value your input. Share your thoughts on the clarity of instructions, the provided dataset, the expected output, and any suggestions to enhance your experience.
Thank you!
