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Challenge #8: Aggregate Consumer Purchases

AK3
7 - Meteor

Another submission

Mac
7 - Meteor

Glad I did this one after lunch instead of before :)

thuydn
6 - Meteoroid

Level: Easy (Prep/Join/Transform tool categories)

Time: 15 minutes

Tip: I found it easiest to break it down to 4 tasks:

1. Filter trans. data since June 2013
2. Get type info per transactions
3. Determine if meal deal criteria is met
4. Calculate totals and percentages

 

Here's a snapshot of my solution - to see full solution download attached .yxzp 

Challenge8_Aggregate Consumer Purchases.PNG

rodalferreira
8 - Asteroid

This was tricky to achieve the same results and after a while I realise the dates criteria in the post and in the workflow are different.

 

My solution:

datamonkey
8 - Asteroid

Nothing like a Monday morning Cross-tab to start the week off on the right note :D

Verakso
11 - Bolide

I did solve this in the end.

 

But it had me confused that the challenge said "tickets since June 2013", if only had read the text on post where it says "orders since July 1, 2013".

Once I used that date, my result matched the output provided

Spoiler
My take on this weekly challengeMy take on this weekly challenge
I am just wondering if there is a faster and quicker way, than all these joins.
One of the paths I took before I came to this solution involved to many unions, which was exponentially taking more and more time to execute.

 //Thomas

 

jbranaum
8 - Asteroid

Here is my solution.

vbrown
8 - Asteroid

I present: my solution!

yajing_wang
8 - Asteroid

use Group concatenate to filter the data

Spoiler
Spoiler
6.PNG
yajing_wang
8 - Asteroid

use Group concatenate to filter the data

Spoiler
Spoiler
6.PNG