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# Weekly Challenges

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## Challenge #8: Aggregate Consumer Purchases

6 - Meteoroid

Hi,

I am new to Alteryx and going through onboarding.

Here's my solution:

5 - Atom

Solution

5 - Atom

1. Select required columns TicketID, Date, Desc from Point of Sale data set.

2. Filter out data by Date criteria (date since June 2013).

3. Join with Lookup table by Desc to get Type (category of food).

4. Go through each record to flag is_pizza_or_burger, is_side, is_drink with value 1 and 0.

5. Aggregate data to get max value of is_pizza_or_burger, is_side, is_drink for each TicketID group (Potential Meal Deal).

6. Go through each aggregated record to falg is_meal_deal with value 1 when each is_xxx flags is 1, otherwise 0.

7. Aggregate data set from setp 6 by TicketID to get total "Potential Meal Deal" count and by is_meal_deal to get total is_meal_deal count .

8. Calculate and show results:

"Potential Meal Deal" - total TicketID count from step 7.

"Total" - total is_meal_deal count from step 7.

"%" - [Total]/[Potential Meal Deal]

7 - Meteor

Hosted a weekly challenge with my team and had fun - Found 3 different ways to solve the problem 2 of which could be done with in-db tools! Lookup Tables, Crosstabs, Date Parse Tools, use of filters and joins.

5 - Atom

Posting as part of Onboarding training.

7 - Meteor

MySolution 008

7 - Meteor

My Solution 008

6 - Meteoroid

Instead of having a separate lookup table, I filtered for the relevant categories and then created a filter for the 3 relevant scenarios.

Separate from the solution, also ended up appending the total unique ticket IDs from Jul 2013 onwards in order to calculate the percentage.

8 - Asteroid

my solution

7 - Meteor

Solution