Hi Community members,

A solution to last week’s challenge can be found here.

This challenge was submitted by Ashley Talay, @aatalai. Thank you, Ash, for this delightful seasonal puzzle!

As the snow begins to fall and the year comes to a cozy close, it’s the perfect time for a bit of holiday fun. While the Elf on the Shelf is busy reporting back to Santa, another mischievous character has gone missing...

Waldo (or Wally, depending on where you’re celebrating) has snuck off for a little hide-and-seek adventure. Guess where? Inside an Excel folder, of all places!

He's somewhere deep within the "Places" directory, but he’s layered himself under folders, subfolders, and buried sheets, a classic Waldo move. We don’t know:

• Which folder he's in,
• Which subfolder he chose,
• What file he’s hiding in,
• Or even which sheet he’s nestled on.

Your mission (should you choose to accept it under the twinkling lights of December):

Find Waldo!

Dig through the maze of folders and spreadsheets, and tell us exactly where he is hiding:

• Folder
• Subfolder
• File name
• Sheet name

If you feel it’s time to showcase your macros skills, you can level up and dive even deeper.

Once you have completed your challenge, include your solution file and a screenshot of your workflow as attachments to your comment.

Good Luck!

The Academy Team

Good evening everyone. Was hoping i could get ideas, or maybe steer me in the right direction, on how to build the below (see screenshot).

I have a numeric field called AMOUNT and i need to be able to create a new field that spells out whatever is in the AMOUNT field.

Is there a tool that will do that? Asked Chatgpt and it told me i need to build a macro, but i'm not the best at building macros. Let me know if anyone has ideas. 

(oh i attached an example alteryx workflow if that helps)

Thanks so much.

A solution to last week's Challenge has been posted HERE!

I learned the worst thing to say to a bunch of football fans: "The Super Bowl?  It's just another football game".   The looks of horror on my colleagues' faces when I said that are burned into my memory forever.  And let me warn you: don't say that when you have anything important to do because you will be subject to an hour-long debate about player stats, offense/defense match-ups, the importance of turnovers (and not just the apple flavored ones) and the proper way to make chili. 

Anyway, after this debate, I did what any data nerd would do: I took to the internet in search of datasets and fired up my Alteryx Designer to answer this question: Is the Super Bowl just another game?  I decided that I'd do a little experiment.  Using the Predictive tools and data from the New England Patriots's 2016 and 2017 seasons, I wanted to see how a linear regression model developed on regular season games (including post-season) performed when used to predict the number of points the Patriots would score during the Super Bowl. 

First, I downloaded data (source: here) for the New England Patriots for the 2016 and 2016 seasons (provided as inputs in the Start File), which required a bit of parsing to prepare for later use.  Then, I set out on some data investigation to begin my linear regression model development.  My approach (which may not be the same one you use in your modeling approach)  was to choose the four (4) variables from the "Score", "Offense" and "Defense" data categories with the most significant relationship to the variable "TM", which indicates the number of points the Patriots scored.  With my variables selected, I began the model creation.  My approach (which may differ from yours😞 develop the model on on values except for one pair of regular season games and the Super Bowl games.

What's the difference between your predicted values and actual values for your regular season games and Super Bowl games?  Is the Super Bowl just another game? 

Extra Challenge: How'd you do on this Jeopardy Category?  Admittedly, I was in good company with these contestants!       

A solution to last week's Challenge can be found here! 

A big thanks to those of you that joined us last week at Inspire for the Weekly Challenge session!  It was so much fun solving with you all! 

This week, we're identifying the most popular baby names that were registered between the years of 1880 and 2017.  Given the provided dataset, determine the most popular names for Males and Females for each available year.  The column "Field_1" contains three concatenated values: the name, the associated gender (Male or Female) and the number of occurrences that the name appeared in birth records.   The column "FileName" contains the name of the file in which the record is found; the data was read in from a zip file that contained text files for each year (1880-2017) of records. 

The solution to last week's challenge can be found HERE!

Just a note:  Santalytics will take over Weekly Challenge the 3 weeks following this challenge. Let me say, it's gonna be exciting (an we secretly have been priming you with some of the more recent challenges)! Stay tuned next week to participate!

This week's challenge is taking advantage of the waning days of November and will bring out one last fall-themed challenge. This particular challenge was conceived, constructed and submitted by the distinguished @NicoleJohnson! Thanks Nicole!

Challenge:

You are promoting a new phone app called PIXL near the T-Mobile campus that tracks the Latitude/Longitude of the photos you take so that you can combine the pictures you've taken with a map of your route. You've given the app to some people in the area so they can test it out, and are tracking various phone data for analysis. Things were going well until about 12:50, when you ordered your favorite drink - a Pumpkin Spice Latte, extra pumpkin, of course - and were just about to sit down at your desk to enjoy your beverage, when you were suddenly pulled away to deal with an emergency logo situation... By the time you made it back 20 minutes later to where you'd left your latte on your desk, your treasured PSL was gone!!! Now you knew people were running all over the area testing out your new app, so you thought perhaps you might be able to use the data you were collecting from the testers to see if anyone in the area had seen your PSL thief...

Using the PIXL Data & image links below, see if you can identify the Pumpkin Spice Latte stealing culprit!!

HINTS:
- Data file is structured with some concatenated information: DateTime (in 24-hour format), Phone Number, Latitude & Longitude where picture was taken, and some other qualifiers & delimiters.

- Data will need to be parsed first to find the relevant fields for analysis.
- Assume that the thief probably couldn't have been farther than .25 miles from the location of the robbery during the time frame in question.
- There will likely be more than one potential thief in the area once you've filtered your results for time & location proximity, so you'll also want to see the images from their PIXL app data in order to narrow down your search!

Hi everyone,

I’m trying to build a Prior Year (PY) Demand Units logic in Alteryx, but my use case is a bit different from standard YoY calculations.

Data Structure

• Data is snapshot-based (not transactional)

• Example snapshots:

  • Mar 7, 2026 → Current Year (CY)

  • Mar 1, 2025 → Prior Year (PY)

• Each snapshot contains:

  • Historical Demand (past weeks)

  • Backlog + SA Units (future weeks)

Requirement

For each snapshot, demand is calculated as:

• If Fiscal Week < Snapshot Week → use Historical Demand

• Else → use Backlog + SA Units

Then:

• CY should use 2026 snapshot

• PY should use 2025 snapshot

• Both should align on Fiscal Month/Week for comparison

Challenge

• PY cannot be calculated using simple Date - 1 year logic

• Because:

  • Data is stored per snapshot

  • Future values differ per snapshot

• I need to:

  1. Join or align snapshots (CY vs PY)

  2. Apply the same conditional logic

  3. Output aligned CY vs PY demand

Question

What is the best approach in Alteryx to:

• Align two snapshots (current vs prior year)?

• Apply conditional logic based on snapshot week?

• Ensure proper week/month alignment for reporting?

Would this be best handled using:

• Multi-Row Formula?

• Self-join on relative week?

• Or a different approach?

Any guidance or workflow examples would be really helpful.

I am currently trying to solve this in Tableau using LOOKUP but facing alignment issues.

Thanks in advance!

Hi all - Is there a tool to convert below months or weeks into days directly please ? For example -1 month = 30 days etc

Thanks in advance!

A solution to last week's Challenge has been posted HERE! 

This year's (2017-2018) flu season has been reported to be the most severe in the past decade.  In particular, influenza-related hospitalizations are on the rise across a wider range of age groups than normal.  For this week's Challenge, we'll use data from the Center for Disease Control (CDC) concerning California's data on influenza-related hospitalizations.  Create a table that shows the cumulative number of hospitalizations per age group for each flu season.

Looking for additional analyses to do?  How about a week-by-week comparison of hospitalizations?  Or perhaps a forecast of the number of expected hospitalizations for a particular age group?  Or maybe a visual representation of the data is up your alley!  

Stay healthy out there!   

A solution to last week's challenge can be found here.GIPHY

Video games have become a ubiquitous part of culture over the past few decades. What started as giant consoles became miniaturized for use at home. As popularity increased and technology advanced, more titles were offered by various companies. Whether you wanted to be a frog hopping across the street, stack odd shapes falling from the sky, or defeat the dreaded space invaders, there was a game for you. 

Over time, many companies innovated with different categories of games which expanded or create new genres. These games were made available for a variety of platforms - the hardware running the games. 

This week's challenge is to parse the provided video game dataset into columns.

Hi All,

I am outputting data from an excel spreadsheet to a SQL table on Alteryx. The challenge I am facing is that the schema changes periodically as I would have additional columns on my excel spreadsheet. Due to this my Alteryx workflow fails to write the data to SQL table. What is the best way to do it ?

Table on week 1

Table on week 2

Hi All.

I am trying to display a custom message on the Alteryx server after a certain condition is met.

Using Message tool is helpful on the Designer but it does not work on the Server.

I have tried using the Output Message option available at the Interface Designer Setting Option but it is not of much help as my message is not a fixed message.

Thank Your for the help in advance.

Thanks and regards
Gouravi Tandel 

Hi I'm developing a standard macro that starts with the user choosing an option from a drop down list. If specfic options are choosen I want there to be a further option of a radio button, any idea as to how to do that please?

I hope everyone is enjoying the Grand Prix series, last week’s (challenge #30) solution is posted HERE.

Here is the Scenario for this lap:  With Inspire being held in beautiful San Diego, I'm planning on taking Friday off and trying out some of the world class surfing! Since it is summer, and I'm definitely a novice, I'd like to visit the surf sites in San Diego County that are appropriate for beginners and summer surfing season. Luckily, I found some datasets on the internet that provide this information.

The objective is to:  Join the site characteristics to the site location data and identify the four locations that are appropriate for a beginner skill level surfing in the summer season.

*Remember to time yourself, contestants only had about tem minutes per lap.

A solution to last week's Challenge can be found here.  

Halloween is just around the corner, and what better way to celebrate than watching a scary movie (with plenty of candy, of course!)?  For this Challenge, you'll find a way to display the images and create snippets for your favorite movie posters (scary or not).  I've chosen to display some posters from classic horror films.  The Crawling Eye?  Anyone?  It's ok...that happens a lot.  

For the Challenge, feel free to replicate the display  for each of the posters I've chosen to share OR create a workflow that displays posters from some of your favorite Halloween films! 

*We updated the start file and the solution file due to the URL link's change.

Hurry! Halloween is almost here!

Hi Gurus,

I want to do a spatial match, but selectively on geofences that match criteria of a transaction.

I have stream of data with points.

I have a set shapes and I want to find what points occur in what shapes.

Easy enough, using a spatial match using target within universe.

Now I want to compare the stream of data with points, but only against criteria the it shares with the geofence.

I have a stream of sales data with a salesperson has an identifier.

I have a set of geofences which don't overlap among 1 salesperson, but may overlap among all salespeople.

I want to compare the location of the salesperson against only their set of geofences.

If then the location isn't within the universe of their own geofences, I then want to do a find nearest, but again only against their own geofences and not everyones.

The best thing I can think of is a batch macro, but just can't seem to figure out if this makes sense to do when processing 20m records. Will each record going through the batch macro then create a new request to fetch the geofence set of each salespersons geofences?

It's such a simple thing to do in my head, just can't figure out the order of the toolset for this.

thanks in advance,

Hi All, 

This is the data, I am working on, payments schedule from a certain date (November 2025 in this instance) 

I need to Dynamically Rename the Column Headers Payment 1, Payment 2 etc to the dates that the payment is done which is usually the next month. I have tried using the Formula option in Dynamic Rename Tool, tried creating a mapping table with dates etc to get the Column header changed but to no avail. I am sure I am messing it up somewhere. 

This would be the desired output: 

I have multiple Sheets in my Excel with Payment plans starting from Sep 2025 till Feb 2026. I tried using the take input from Right Rows option but found it very limiting since I would have to keep changing the data every month when we create it for a new month and it is not dynamic in that sense. 

Can help me set this up please? 

Hi,

I hope someone can help as I have searched the community and none of the solutions provided appears to work. I have a string field of the format below

2026-03-11 12:00RACEDAY

What Im trying to do is search for date using filter and true/false. This will filter out all fields with this format, then I need to parse date and time. The "raceday" word is not common across all the fields.

Any help would be much appreciated. 

Thank you

The link to last week’s challenge (challenge #28) is HERE

Hi everyone, what an awesome time we had at the Alteryx Inspire 2016 Conference in San Diego last week.  It was so nice to meet many of the Community members in person.  If you attended the conference and went to the Grand Prix event, this week’s challenge is the first of the four laps.  We will cover all of laps as weekly challenges in the next weeks.   See if you have what it takes to compete, keep in mind the contestants only had about 10 minutes per lap maximum so maybe time yourself.

Use Case:  You are the commissioner for your fantasy baseball team. You recently completed your draft and you want to run some simple statistics about each fantasy team.

You have 3 inputs

1) Fantasy pick summary from your draft

2) Hitter stats on all field players (whether selected in your draft or not)

3) Pitchers stats on all pitchers (whether selected in your draft or not)

Objective:  In order to run some stats on your draft, you first need to prep your data. Please combine all 3 files so that you have a single output that contains stats on each player drafted in your draft, ordered by "Overall_Pick."

Drivers start your engines!

Welcome to 2016 we hope you are enjoying these challenges. The link to the solution for last challenge #6 is here. For the seventh challenge let’s look at downloading data with an API and parsing that data from JSON into a usable format.

The data we will use comes from Quandl. The Quandl site offers access to several million financial, economic and social datasets. Data is indexed from multiple sources allowing users to find and download in various formats. All Quandl's data are accessible via an API.

For this example the response from these APIs is JSON. Our user is trying to get aggregated Annual Outbound Tourism Statistics for the US dating back to 1995. The Text Input contains the URL for the API request. Your goal is to parse the response.

Hint: After parsing the JSON, you will need to further identify the patterns within the data to effectively stage into a table for analytics.

Note: The data in the API is subject to change. When trying to match the output, the effort should be focused on achieving an identically structured dataset. 

We have listed this as an advanced challenge since configuring the download tool and parsing functions are more advanced topics. We are looking forward to hearing your feedback.

UPDATE 1/11/2016: the solution to this exercise can be found below.

UPDATE 4/10/2019: Previous API link expired. Exercise updated to new API.

This is a series of blogs that shows how one can use AI with Alteryx. This second article focuses on workflow XML analysis with LLMs, this time focused on comparing workflows to see differences!

Introduction

Alteryx helps automate data processes through workflows. These workflows are saved as XML files, which capture all configurations and connections, making it easier to analyze and document them.

Building on my previous blog post, AI Meets Alteryx: Exploring XML Automation and Insights, we will explore how to compare Alteryx workflows using AI. By leveraging Large Language Models (LLMs), we can gain valuable insights from XML files to enhance our data processes.

Let’s dive into these techniques and see how AI can make your Alteryx workflows more efficient!

The Role of LLMs in XML Comparison

Large Language Models (LLMs) have transformed the way we process and analyze textual data, and their application extends to understanding structured data formats like XML. Here’s how LLMs can assist in comparing Alteryx workflows:

• Natural Language Understanding: LLMs can interpret the semantics of XML tags and attributes, allowing them to grasp the meaning behind the data rather than just its structure. This capability is essential for understanding the context of changes in workflows.
  
  
• Contextual Awareness: When comparing two XML files, LLMs can leverage their contextual understanding to identify not just differences but also the implications of those differences. For example, changing a tool configuration might have downstream effects in the workflow.
  
  
• Prompt Engineering: By crafting specific prompts, users can guide LLMs to focus on particular aspects of the XML, such as tool configurations or connections. This targeted approach can yield more relevant insights during comparisons.
  
  
• Error Detection: LLMs can assist in identifying potential errors or inconsistencies in workflows by comparing expected configurations against actual XML representations.

Before going towards the fun stuff with AI, there are some key points to consider:

• XML Structure: Dive deep into the common elements in Alteryx XML files, such as tools, connections, and configuration settings. These elements will serve as the backbone of the comparison to work.

• LLM Training: Discuss how LLMs can be fine-tuned or prompted to understand specific XML structures. LLMs are still not perfect and will require fine-tuning to get the desired output.

• Comparison Techniques: Explore different strategies for comparing XML files, including visualization of differences and optimization reports.

• User Experience: Consider how this approach can enhance user experience, especially for users who may not be familiar with XML.

Methodology

To effectively compare Alteryx workflows using LLMs, follow these steps:

Step 1: Extract XML from Alteryx Workflows

• Have two workflows that you want to compare. In this example, I created two workflows called WF1 and WF1_v2. It is a random workflow with a few tools and random procedures (as an example).

 Source: Alteryx Designer Sample Workflow - caltang’s WF1

Source: Alteryx Designer Sample Workflow - caltang’s WF1_v2

Once you have two workflows, you can open them via Notepad or Notepad++ and save them as XML files like below:

Source: caltang screenshot

Step 2: Load the XML Files

• It is time to load the XML files into your LLM of choice. Once again, I will be opting to use Poe!
• The prompt which kickstarts this process is:

Prompt: “Goal: To compare the differences between two Alteryx workflows by way of XML differences. Action: I will provide you with two workflow XMLs for comparison.”

Source: caltang’s Poe screenshot

• Then, load the XMLs into the LLM with a high-level prompt:

Prompt: “WF1_xml contains the original workflow. WF1_v2_xml is the changed version of WF1. Please study the files and provide a simple breakdown of the differences at a glance.”

Source: caltang’s Poe screenshot

• Then, review the output generated by the LLM. Focus on the insights it provides regarding changes, implications, and any potential errors.

Source: caltang’s Poe screenshot

Source: caltang’s Poe screenshot

Source: caltang’s Poe screenshot

• You can try with different prompts as well! Here are some examples of prompts you could use to guide the LLM:
  • “What are the significant differences between these two workflow XMLs?”
  • “Explain how changes in the tool configuration might affect the overall workflow.”
  • “Identify any potential errors based on the following XML structures.”

Advanced Functionalities

Visualization of Differences

To go a step beyond what was shown, there needs to be more thought about the output from this exercise. In this example, I will go for a visualization and a report from the XMLs compared.

Source: caltang’s Poe screenshot

As you can see, LLMs are still not perfect as they can generate images but with gibberish words. This will not do. Trying again:

Source: caltang’s Poe screenshot

As you can see, although some words are readable, most of the image is still gibberish. Instead of going for an image, let us go for Python code!

Source: caltang’s Poe screenshot

Now, with Python code, it is easier to test and see the code firsthand! Code refactoring and optimization can be done later - but the beauty of getting this code is that it comes with some documentation as well:

Source: caltang’s Poe screenshot

You can then try running the Python code and see your output:

Source: caltang’s Poe screenshot - Python Output

As you can see, the Python code highlights the positions of WF1 and WF1_v2 and points out the expression change done in the filter tool. To go further, more experimentation is needed!

Explanation of Differences

Visualization of the differences is helpful to give a quick overview/glance of the situation. But the devil is always in the details! Imagine a scenario where you have over 100 tools in a workflow, and each of them has changed in terms of expressions, settings, and selections within the tool configurations. It will be a nightmare to go through each one!

That is where LLMs can help! Try doing it this way:

Prompt: “Goal: I want to have a report of the differences seen in expressions, tool configurations, tool locations, and the presence of tool containers or not. Please list them out and explain what has changed, and give your analysis on the change - whether it is optimized or not - and explain why you recommend those changes.”

This is the response by the LLM:

Here's a structured report of the differences observed in the Alteryx workflows, focusing on expressions, tool configurations, tool locations, and the presence of tool containers.

Report on Workflow Changes

1. Expressions

• Original Expression: Simple mode with date conditions in the Filter tool.
• Updated Expression: Changed to Custom mode with the expression [Name] IN (...).

Analysis:

• Change: The expression was adapted from a simple filtering mechanism to a more complex custom condition, allowing for greater flexibility in data selection.
• Optimization: This change is optimized as it can handle more complex filtering criteria, making the workflow more versatile.
• Recommendation: This is a positive change as it enhances the filtering logic, allowing users to include multiple conditions in one expression, which can lead to more efficient data processing.

2. Tool Configurations

• Original Configuration: The Filter tool was set to a simple mode.
• Updated Configuration: The Filter tool is now set to custom mode.

Analysis:

• Change: The configuration has shifted from a straightforward filter to a customizable one.
• Optimization: This is an optimized change as it allows for more tailored data manipulation.
• Recommendation: It is advisable to utilize custom configurations when the data requirements are complex, as this can improve the accuracy of data outputs.

3. Tool Locations

• Original Tool Locations:
  • Input: (138, 126)
  • Transpose: (246, 126)
  • Filter: (378, 126)
  • Histogram: (522, 114)
  • Browse: (630, 114)

• Updated Tool Locations:
  • Step 1: Input: (89, 77)
  • Step 2: Transformation: (269, 65)
  • Step 3: Output: (689, 65)
  • Transpose: (294, 126)
  • Filter: (426, 126)
  • Histogram: (570, 114)
  • Browse: (714, 114)

Analysis:

• Change: Nodes have been repositioned significantly, especially the Input and Output nodes.
• Optimization: The new layout provides a clearer flow of data from Input to Output, which can enhance readability and maintenance of the workflow.
• Recommendation: Maintaining a logical flow in node placement is crucial for clarity. The updated positions are better organized, facilitating easier debugging and understanding of the workflow.

4. Presence of Tool Containers

• Original Workflow: No explicit tool containers were mentioned.
• Updated Workflow: Presence of tool containers is implied as workflows are organized into steps.

Analysis:

• Change: The updated workflow appears to have a more modular design with clear step delineations.
• Optimization: Using tool containers can help in organizing workflows and improving manageability, especially in complex projects.
• Recommendation: Implementing tool containers is advisable for larger workflows to encapsulate related tools. This organization can improve performance and clarity, allowing users to focus on specific segments of the workflow without distraction.

Overall Recommendation

The changes made in the updated workflow are largely positive, enhancing flexibility, clarity, and manageability. The shift to custom filtering allows for more robust data processing, while reorganizing tool locations improves workflow readability. Adopting tool containers can further enhance organization, especially as workflows grow in complexity.

Conclusion

These adjustments indicate a thoughtful approach to optimizing workflow efficiency and clarity in Alteryx. It is recommended to continue evaluating workflow structures regularly to ensure they meet evolving data processing needs effectively.

Conclusion

Integrating AI into Alteryx workflow analysis enhances efficiency and clarity. By using Large Language Models (LLMs) to examine XML files, we can easily identify changes and gain insights into our data processes.

This approach simplifies workflow comparisons and streamlines documentation. Embrace these techniques to optimize your Alteryx projects and improve your data management practices!

This article was inspired by my work with Vicky (@Vicky_Lau) - her questions and curiosity led me to experiment with this solution that I now use every day. Now, everyone will be able to use this as well.

A solution to last week's challenge can be found here.

This week's challenge was shared by @LordNeilLord  and @JReid  from an original post by @AnandKumar1. Thanks to all of you for sharing this challenge!

This challenge includes two inputs: 1) An equation written in Roman numerals and 2) a look-up table of certain Roman numerals. Solve the equation and return the answer as an integer.

Update: Start file updated on 10/1/2019

Hi - The excel output contains the multiple tabs all tabs contains the different fields/Data. how can i save the file with all tabs in sharepoint ? could you please guide me on this ?

 I've setup like this but I keep getting empty data. Am I doing something wrong or is this not possible 

A solution to last week’s challenge can be found here.

To solve this week’s challenge, use Designer Cloud or Designer Desktop.

Haven’t heard about Designer Cloud yet? Watch a demo.

How often do you get to be the judge of a Pokémon video game tournament? How well do you know your Pokémons?

In this challenge, you will determine who qualifies as a Pokémon trainer for a tournament! Pokémon are virtual creatures living with human partners called “trainers.”

Let's introduce you to the concept of Pokémon types. Types are properties applied to Pokémon and their moves, which affect the power of moves in battles. There are 18 types: Normal, Fire, Fighting, Water, Flying, Grass, Poison, Electric, Ground, Psychic, Rock, Ice, Bug, Dragon, Ghost, Dark, Steel, and Fairy. A Pokémon may have either one or two types. For instance, Charmander is a Fire type, while Bulbasaur is both a Grass type and a Poison type. There are a total of 324 possible ways to assign types to a Pokémon.

To qualify as a trainer in the tournament, you must have at least eight Pokémon types total, ranging across your six-Pokémon roster.
The dataset Pokemon trainers contains information on four Pokémon trainers and their six Pokémon.
The dataset Pokedex contains information on all Pokémons from all generations, such as the type (or types) of the Pokémon.

Your challenge is to determine which trainers qualify for the tournament and list the trainers' names and their six Pokémons (eight Pokémon types total).

Thank you for your comment @Jean-Balteryx . The start file was updated.

A solution to last week's challenge can be found here! 

This week's challenge comes to us from ACE @patrick_digan. 

Using the provided URL, download and parse the data in the recipe for an Old Southern. Create a list of the cocktail ingredients and measurements.

Whiskey (and other spirits) and analytics go surprisingly well together.  Head on over to our Events page to join an evening of whiskey tasting and data sampling near you. 

I prefer my analytics shaken...not stirred.

Hi Team,

While preparing the Alteryx WF, I have two output files "Invoice overview report" & "Journal N detail" where in "WBS Reference 2" are common in both the files. but I want the data like as "Required Data" file in which both the data merge in one separate TAB on the basis of "WBS Reference 2". Refer all three files.

Regards,

Mahesh

A solution to last week's challenge can be found here. Source: https://en.wikipedia.org/wiki/Gender

In general, there are slightly more men than women in the world. According to the United Nations, the number of men is rising gradually each year since 1960. However, some statistics show this is not the case in certain countries. In former Soviet republics, for example, women outnumber men. Conversely, there are more men than women in Asia, Arab countries, and Northern Africa, but what about in Latin America?

This Input data for this challenge is an Excel file containing data with the long-term population estimates and projections from 1950 to 2100. Use it to answer the following questions:

1. What was the last year in which there were more men than women in a Latin American country?
2. In what year will the percentage of men in a Latin American country reach the lowest point according to this dataset?
3. Is there any chance that it will be more men than women by 2100? In which Latin American country?