BI: Lessons Learned

  Well this week I am keeping it simple because of some other commitments. For week 17, I had two pieces of information that I scratched my head about. The first is something that is key as a data analyst.. to pivot your data. Tableau loves data to be nicely organized into rows. This is the data as delivered from Data World.  As you can see the data has many columns for each of the 'categories' of popcorn.  This makes the data difficult to work with as columns in tableau.  So, typically we will pivot the data so it is in rows.  In the example below, this is the end result we wanted to reach. Each team has a category and score assigned.   To get there all we had to do was  1.go to your data tab 2.select (Control + left mouse click) the rows we wanted to pivot 3.Right Click 4.Pivot Data wala! The last thing that I got stuck on was I was doing a dual axis chart and I couldn't get the data to present itself right.  I needed to change a measure to a

 So, I've been a bit out of pocket for weeks due to some personal stuff going on that I am sure I'll blog about in the near future.  In the meantime, here is my thoughts on MM_Week15.  I created a small multiple chart this week with help from Daniel Foster and a TTipTuesday from Andy Kriebel.  Here are my notes and the link ;  This is what is in the Columns & Rows.  The tutorial link explains the Column\row formulas. The Sum(-20) is a dual axis for alignment purposes.  This is the formulas for the Column\Row s; nCols = 10 Column Divider = //(INDEX()-1)%(ROUND(SQRT(SIZE()))) // uses display size (INDEX()-1)% [nCols] Row Divider = //INT((INDEX()-1)/(ROUND(SQRT(SIZE())))) // uses display size INT((INDEX()-1)/[nCols]) Created a parameter to break out the descriptive    NOTE: made mistake on the 2 field above and so had nulls for my rank and service level rank Formula for Rank = CASE [Choose Ranking] WHEN 'Cashrank&