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Hi Maveryx,
A solution to last week’s challenge can be found here.
This challenge was submitted by Patrick Digan (@patrick_digan) an Alteryx ACE and also an active Community member who has contributed to many challenges before. Thank you, Patrick!
This week’s challenge is inspired by a special day that just passed: Pi Day! Not the delicious treat, but the number with an infinite sequence of non-repeating decimals: 3.14, which is celebrated on March 14.
In honor of pi, this week your task is to find all 13 numbers less than or equal to 100,000 that are equal to the n th power of the sum of their digits. For example, 81 is a 2-digit number, so n=2, and (8+1) 2 = 81; therefore, it falls under the category we are looking for.
For the input, use the Generate Rows tool to generate numbers from 0 to 100,000.
Bonus question: If you want to take your skills to the next level, you are invited to find all 17 numbers that are equal to any n th power of the sum of its digits. For example, 4,913 works for this. While it will fail for the first task because (4 + 9 + 1 + 3) 4 = 83,521, the number 4,913 works well for the bonus question since (4 + 9 + 1 + 3) 3 = 4,913.
Need a refresher? Review these lessons in Academy to gear up:
Summarizing Data
Creating Regular Expressions
Good luck!
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Here is this week’s challenge, I would like to thank everyone for playing along and for your feedback. You can find the solution to the previous challenge here.
For this challenge let’s look at creating a multi-level hierarchy from employee-manager data. As always there are several ways to do this challenge, I have designated it as an advanced challenge because there is an elegant way to solve it using iterative macros. The advantage to the iterative macro solution is that it becomes very dynamic. Other hard coded solutions would get you to the answer with this data, but if the depth of the hierarchy were to change, you would have to modify the workflow to support the change. It is a great example to see how iterative macros can make a workflow dynamic.
The use case:
An HR department wants to use Alteryx to quickly understand the reporting structure for employees across their organization.
The Input source contains 5 employees and an identifier that uniquely identifies the individual and the manager they report to.
The goal is to create a hierarchy field identifying each relationship between employee and manager(s). For example, a Director reports directly to the Vice President which is 1 level up. The Director is then 2 levels away from the CEO (in this data set). As a result the hierarchy identifier represents how many levels removed the employee is from management team they report into.
Give it a try, I look forward to your feedback.
UPDATED 2/16/2016:
The Solution has been included.
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The link to last week’s exercise (exercise #45) is HERE
I love to share real world use cases as exercises. This week’s exercise comes from a customer that had data coming from in a legacy system and needed to transform the date field for a new system. It is a straightforward exercise but shows how easily Alteryx can apply business logic to most any data transformation problem.
Use case: The Input contains dates formatted as year, month and day. In this case, the first character determines if the year should begin with 19 or 20. If the first character is 0 then the year starts with 19, and when the first character is 1 the year starts with 20. The remainder of the date following the 0 or 1 is the remaining year digits followed by month followed by day.
Objective: Please convert these strings into date formatted field.
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We hope you enjoyed last week's challenge. The solution has been posted here. For the second challenge lets look at removing characters and splitting data into columns based on delimiters.
Many products will export textual data with delimiters such as quotes. This is done so that strings can contain delimiters or control characters within them. Having more than one type of delimiter can be hard for ETL programs to interpret. In the input text file, there are two different delimiters (double quotes, single quotes) and they surround different data types.
Use Alteryx to strip out the delimiters as superfluous and format the data as represented in the output.
You may notice that we have started classifying the exercises into beginner, Intermediate and advanced. This classification is used by Alteryx internally to sequence exercises as users advance.
Update 11/23/2015:
The solution has been uploaded.
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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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