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A solution to last week's challenge can be found here.
This week's challenge marks the culmination of a trilogy of challenges inspired by the 2023 Inspire Grand Prix. These challenges explore real-world scenarios that many companies frequently face. The previous week's challenge involved a spatial problem, while the week prior focused on data preparation and integration. In this concluding challenge, we will delve into 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 answer! Remember to share your time when you submit your workflow.
Let’s start now: 3, 2, 1, Go!
A driver who works for ACE was recently promoted to shift manager, so the company needs to reduce their weekly food collection schedule by five shifts until they can fill the driver position.
1. Which five shifts are most likely to be unsuccessful?
Build a random forest model to determine the five collection shifts with the highest likelihood of having a cancellation based on historical job data. For the forest model, use only the DistanceMiles, Hour, and DayofWeek columns as your predictors.
For the cancellation data, you will need the calculate the following:
DayofWeek: The exact field name, full name of the day, and (%A) the job occurred based on the Date.
JobStatus:
• A value of Unsuccessful if the job was canceled. • A value of Successful if the job was successful based on ClosedReason values. A Successful value would be any ClosedReason starting with 01 or 02 and an Unsuccessful value would be any other value.
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A solution to last week's challenge can be found here!
This week's challenge will look familiar for those that attended Inspire this year. And for those that competed or were pit crew, you'll know this one well.
For those that have never attended Inspire, we have a contest among the fastest Alteryx users on stage in front of the entire Inspire audience. This year, roughly 5000 attendees watched as the 5 finalists competed to solve each Heat.
Although you won't have the aid of a pit crew to help you along the way, feel free to time yourself as you try complete this workflow. Give yourself about 2-3 minutes to read and understand the question, then start the clock. At the 11-minute mark, you may open up the tool contained named "Turbo Boost" which will reveal roughly 75% of a completed solution. Use this however you want.
For those that plan to attend Inspire Europe, keep your eyes peeled on the Analytics Blog to register for the Grand Prix Europe!
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Happy 2019! Your first weekly challenge of the year is a question from the 2018 EMEA Grand Prix preliminary round. You are tasked with building a time series model to predict how many units of a product should be stocked in the future to keep up with demand.
And, if you hadn't heard, we are hosting our first ever APAC Grand Prix at the Inspire on Tour event in Sydney on 21 March 2019. So if you plan to join us in Sydney, head over the Grand Prix blog and sign yourself up for the preliminary round.
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Hi Maveryx,
A solution to last week’s challenge can be found here.
Don't forget that we are running a campaign inviting all of you to contribute to our upcoming 2024 Weekly Challenges! Your ideas and participation are crucial in shaping an engaging and innovative year ahead. Visit our blog post to review the guidelines and submit your challenge to earn our brand-new accolade, the Weekly Challenge Contributor Badge!
A special thanks to Mark Thompson (@Watermark) for submitting this challenge some time ago. Your contribution is greatly appreciated, Mark! It is a fantastic opportunity for our users to test and enhance their RegEx tool skills.
Your company recently adopted a new customer relationship management (CRM) tool but overlooked a crucial detail: how to link company records in the new CRM to the companies in the legacy financial system. The common link between these systems is the company’s URL, but the website data entered by the sales team in the CRM is inconsistent and often incorrect.
As the person responsible for solving this issue, your tasks are to:
Match each company in the legacy financial system with its corresponding record in the new CRM.
Analyze the CRM data to identify how many entries contain “dirty data,” meaning entries with subdirectories in the URL.
Determine the number of distinct websites (base URL) that matched during the data integration process.
Identify companies within the US that have multiple opportunities in the CRM (more than one). (Hint: Use the domain URL.)
Identify companies with multiple opportunities (more than one) outside of the US.
Hint: To identify the countries, look for two-character top-level domain (TLD) codes in the URLs. Assume that any other code (for example, .com, .net, or .org) is associated with a US-based company.
If you want to learn how to use regular expressions to parse your data, you can review the following lessons in Academy:
Using RegEx in Expressions
Creating Regular Expressions
Parsing Data with RegEx
Good luck!
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A solution to last week’s challenge can be found here.
Welcome to the Good Ladies weekly challenge!
Five women heist a jewelry store and steal a precious gem in the shape of a ball of yarn.
In the dataset, the 5 women responsible for the heist have been negligent and left clues behind. You are the detective on the case who is looking for these clues in a dataset.
1. Fingerprints on the glass surrounding the gem show fingerprints belonging to someone with the letters "Fled" in their first name or last name.
2. IT Department at the police is able to find that the back door lock password was changed to "ugfsjsh".
3. The vault holding the gem was blown open with "dynamic" dynamite. Found in the ruble is a business card piece. You can make out the first few letters of the word "Bogi"
4. The security guard's witness statement states that he has been vigilant about watching the store. There was only one instance last week when he was distracted by a woman with brunette hair who worked at a wireless store. He remembered later that she'd dropped a handkerchief that had the initials B.K. on it.
5. A slogan was left behind that said, "Those that synergize together can accomplish much and receive the TORPHY."
First, you will have to parse the data.
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