Hi Maveryx,
Welcome to your very first Cloud Quest! This initiative is a thrilling journey into the world of the Alteryx Analytics Cloud, and we are kicking things off with a focus on Alteryx Designer Cloud. These new quests are not only tests of your skills but also opportunities to delve deeper into the practical uses of Designer Cloud in handling real-world data issues.
In the world of data processing, text files often include quotes, which are commonly used to manage strings. This can pose a unique challenge for extract, transform, and load (ETL) programs due to the presence of multiple character types.
In this quest, you have a CSV file containing two rows of concatenated data that include double quotes, single quotes, and commas, which enclose different data types. Use Designer Cloud to separate the data into three different columns: Poem, Poem ID, and Poem Read Date. Refer to the image below to see how your solution should look.
If you find yourself struggling with any of the tasks, feel free to explore these interactive lessons in Maveryx Academy for guidance:
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
First cloud one is in the books.
.fun challenge, couldnt figure out how to downlaod the file 😅, excited for the future of cloud challenges!
Enjoyed the cloud experience for this one. Looking forward to seeing how things hold up as challenges get more complex.
My first ever Cloud Quest!
A simple case of text-to-columns to split into three columns based on a comma (not in quotes), then using a replace formula to remove the quotes from the Peom text and Date fields.
Then I converted the date and dropped the unwanted columns: