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Dive into new analytics techniques with lessons that incorporate videos, hands-on activities and quizzes to assess your knowledge.
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A solution to last week’s challenge can be found here. Source: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-to-make-cloth-face-covering.html
With the sudden need for masks around the globe, sewing has seen an increase in popularity. Many local communities have asked their citizens to pitch in and provide masks to create a sufficient supply. These masks are usually created by sewing a pattern with at least 2 layers of fabric.
In the attached datasets, we have the number of masks created by a local community known as Bastille St. Below that, we also have the number of masks created by local companies and independent contractors for the same community. Use this data to find the total number of masks produced by each group for each mask size and the total number of masks produced by each group.
As a bonus challenge, use the additional table of fabric requirements to determine the total number of cotton bundles that were used by each individual/group. Each bundle of cotton is 122cm x 100 cm and color coded so you can only use each bundle for one size of mask. Remember that they are 2 layers thick!
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The link to last week’s challenge is HERE.
Happy thanksgiving to the USA based challenge participants, hopefully you are hungry for another exercise. This week we will continue with some more data parsing and preparation with survey data. Enjoy!
Use Case: The 2 sources of data contain survey information. The Data input contains all of the survey responses. The Questions input contains the associated questions.
The column (called Column) in the Questions file corresponds to the field header value in the Data file, so value 38 in the Questions files is the questions associated with field F38 in the Data file.
The first row in the Data file contains the response type. In field F38, the data is formatted as Response (Scale 1-10) - Age Range.
Objective: Create an output file for a visualization tool (Tableau, Qlik, PowerBI) that details the response by age for each individual.
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The link to last week’s challenge is HERE.
This week’s exercise is another example of how Alteryx can take poorly formatted data such as transactional log files and turn it into usable data.
Use Case: A customer has some data that comes with key product information stored at the top of the file. Each data column contains three lines of header information per product (product, market and type). The customer wants this information to be shown in rows for each product.
Objective: Reformat the input data to match the output example.
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Here is a new challenge for this week. The link to the solution for last week’s challenge is HERE.
The use case:
We received some text data and that includes an embedded line-feed character.
The objective is to remove the new line character, convert the date-time string to a date-time formatted field and then do some renaming per the sample output.
Good luck, I look forward to your feedback.
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Here is a new challenge for this week, it is a continuation from last week’s warehouse distribution challenge. If you did not complete last week’s challegne don’t worry, you will not need any output from part one to complete this part. The link to the solution for last week’s challenge is HERE. I posted two solutions for last week’s challenge. The first is a solution without a macro and is in my opinion a more straight forward approach to solving the problem. I included the second macro approach because it is an excellent example of how to utilize an iterative macro.
The use case:
Based on data from last week’s warehouse distribution challenge, we want to calculate the total shipped miles per item. The products are available from 3 different warehouses, lat/lon data is provide for each warehouse and each store location.
Your goal is to find the total distance travelled as straight line miles for each item based on it being shipped from the closest warehouse.
Good luck, I hope you are having fun with these challenge and expanding your knowledge of Alteryx. Thanks to all that have provided feedback.
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