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A solution to last week's challenge can be found here.
This week's challenge marks the beginning of a trilogy of challenges inspired by the 2023 Inspire Grand Prix. These challenges delve into real-life scenarios that numerous companies encounter on a regular basis. The initial challenge focuses on the preparation and integration of data, and the second challenge revolves around spatial problem-solving. The third and final challenge entails tackling a predictive case.
If you are eager to experience the same exhilaration our racers feel in Las Vegas, take a quick, 2-minute glance at the instructions, start your timer, and record how long it takes you to determine the correct answers! Remember to share your time when you submit your workflow.
Let’s start now: 3, 2, 1, Go!
A company called ACE collects donated food products and delivers them to customers in different locations. They calculate the weight of each product by product type. Using the provided datasets:
Considering only trips where products were collected with a successful Closed Reason, determine the highest total weight collected by a customer on a single day (all product types combined).
What is the highest weight of product collected from a single customer on a single day? Note that some customers have multiple trips in a day.
What is that customer's ID and the collection date?
Next, calculate the total successfully collected weight for all customers on that date.
What is the total weight of products collected from all customers that day?
What percentage (for example 23%, not 0.23) of the products collected that day did the customer from Question 1 contribute? Round your answer to the nearest integer.
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This challenge comes to us from @Kenda . Thank you for your contribution, Kenda!
Use Designer Desktop or Designer Cloud, Trifacta Classic to solve this week's challenge.
Imagine you work as a data analyst for a company that develops video games. They want to create a strategy to increase profitability. The company has asked you to use industry sales data to determine whether the number of new video games released by a company impacts its profit for that year. You have a dataset (video_game_data.csv) that contains historical sales data of video games by multiple publishers around the world across several platforms. Your challenge is to do the following:
• Determine the years when the same video game publisher released the most game titles (based on the exact value in the Name column) AND had the most sales globally (a value you need to calculate).
Source: https://www.kaggle.com/datasets/gregorut/videogamesales
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A solution to last week's challenge can be found here.
Use Designer Desktop or Designer Cloud, Trifacta Classic to solve this week's challenge.
Are you ready to showcase your analytical skills and uncover valuable insights from the exciting world of international women’s football (or soccer as it is called in the United States)? This Weekly Challenge will put your data manipulation and analysis prowess to the test.
We will be using data gathered from over 4,000 women’s football match results from around the world.
Your challenge is to create a league table, for only the FIFA World Cup tournaments, that pulls together a number of statistics for each team: Games Played (GP), Wins, Draws, Losses, Goals For (GF), Goals Against (GA), Win %, and Average Goals scored per game. From this table, you will be able to answer three intriguing questions:
Which team has the best winning percentage at World Cup tournaments?
Which team scores the most goals on average?
Which team has the worst defense; that is, the most goals conceded?
Using the shootouts.csv dataset, we would also like you to answer this question on penalty shootouts:
Which team has the best penalty shootout performance?
Source: Kaggle Women's International Football Results
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A solution to last week’s challenge can be found here. Source: https://www.dailymail.co.uk/news/article-4965690/Humpback-whale-breaches-Sydney-Harbour-sunset.html
Every year whales around the world migrate from their feeding grounds to their breeding grounds. Some species travel an outstanding 12,000 miles round trip!
Use the data sets below to analyze migration movements for different whale species.
The file Whale_Migration_Data contains a list of whales whose migration patterns have been tracked from 2001-2003, and the total kilometers each whale swam on each day of their migration.
The file Whale_Pods contains a list of whale ids and pod ids, which indicates the pod each whale belongs to.
The file Whale_Species contains information about the whale species of each pod.
Find the total number of kilometers each pod swam for migration for each year, then find the average number of kilometers each whale in that pod swam (total kilometers / number of whales in the pod). Then, find the pod with the highest average kilometers swam per whale for each species for each year.
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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.
Hint: A combination of Formula, Text to Columns, and Select tools should be suffice to solve your problem!
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 Connection 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
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