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Weekly Challenge

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Challenge #1: Join to Range

8 - Asteroid

Don't know why I didn't start this sooner!

I parsed the ranges differently, but otherwise my solution follows the pattern of the example solution.

6 - Meteoroid

Nice challenge, find my solution below.

Spoiler

I used the Tile tool to create 5 manual buckets and then a Formula tool to prefix the letter "R" to the generated [Tile_Num] field. I then joined the two tables on this newly created "Region" field and the pre-existing "Region" field in the other dataset and used a Summarize tool to get the required results.

8 - Asteroid

One down, many to go...

Spoiler
5 - Atom

Success on my first! One good way to do this.

7 - Meteor

Solution for Challenge #1 as per attached.

12 - Quasar

My first intermediate and I think my solution is pretty long-winded!

Spoiler
Text to columns to split the range, rename the new columns to make it easier, count the postal codes, generate rows, use a MRF to identify which rows were errors, then filter them out, formula to create the postal code from start of the range + row number, rename the fields, join with the customer data (after adding a tally column), and sum to result.

9 - Comet

My first instinct was that we really need a tool that can handle flexible join conditions other than A=B.  Then I decided to use the Append function to essentially do a cross product between the range data and the customer file.  I was able to get this to work, but after reading some of the posts I realized this approach was very limited and would not scale well if we had a large set of regions.  My final approach used generate rows and then a standard join, giving a much more scalable approach.

7 - Meteor

7 - Meteor

Hi,

Here is my solution.

Regards,

Patrick Fredin

Spoiler

5 - Atom

First time using the Generate Rows function!

It was a good introduction to the tool :)