Tableau Prep Tiles: New in Tableau 2021.4

0:00Hey Tim here, in 21.4 Tableau have added t

0:02iling to Tableau Prep. Now if you're not

0:04familiar with

0:05tiles this is something that's been used in

0:07Tableau, sorry Tableau, all tricks for a

0:10while

0:10and essentially tiling allows you to create

0:13groups of a specified size equally across

0:15your whole

0:16data set. So what I'm going to do is show

0:18you how to use this inside of Tableau Prep.

0:20It's not a new

0:21type of you know object here in Tableau

0:23Prep, it's not one of these new items here

0:27in this sort of

0:27drop down list, it's just a function that

0:29you can use inside of a calculation. So let

0:32's find out how

0:32to use it. Here in this flow I've been just

0:34using a standard flow, I'd actually just

0:36use this to show

0:37the parameter capability in Tableau Prep. I

0:39actually apply the parameter right here, so

0:42what

0:42I'm going to do is add this new function

0:44right before that step because I want to

0:46keep this

0:46context in my whole entire data set. So I

0:49'll go ahead and hit a plus here and just

0:51add a clean

0:52step and you can see that Tableau Prep

0:54makes space in my flow for me. Now to use

0:57this new function

0:58you do need to create a calculation, so let

1:00's go ahead and create a calculation and the

1:02thing you

1:03want to do here is just go to the

1:04analytical functions in here and you can

1:07see that there's

1:08the nTile function, this is what we're

1:10actually going to be using. Now I have to

1:13say the nTile

1:13function uses a group of functions I'm not

1:15really fond of, I think I find them really

1:18cumbersome to

1:18use. The partitioning and order by

1:21functions in this particular version are

1:24fine, they do

1:25exactly what they say on the tin and in

1:26fact in previous versions they didn't do

1:28what they said

1:29on the tin, there's a bit of a bug there

1:30for a while but nonetheless they do work

1:32now and now

1:33what you can do is you can essentially put

1:36the nTile function inside of this partition

1:39and order

1:39by setup here to essentially specify the

1:42number of groups you'd like once you've

1:44ordered your data

1:46using a particular partition. So what the

1:48partition does is essentially defines your

1:50groups,

1:51your order by essentially decides the rank

1:53of those particular things and then the

1:56ascending

1:57or descending decides the direction whether

1:58you're going from the bottom to the top or

2:00from the top

2:01to the bottom and the nTile is just

2:03essentially then taking that final list and

2:05dividing it into

2:06the equal number of whatever you specify,

2:09so here you'll see it says three and once

2:11it's divided it

2:12into three groups it gives them a number

2:14one two three if I say 10 it will say one

2:16two three four

2:17five six seven eight nine ten. So you sort

2:19of hopefully get the idea here, so what we

2:20're going

2:20to do to keep this super simple, so I'm

2:23just going to make sure that I use this

2:26function that you can

2:27see on screen so you've got a reference

2:28point and I can actually walk you through

2:30it. So let's go

2:31ahead and start typing, let's open up those

2:33curly brackets, let's see if we can make

2:35this larger,

2:35I can make the whole thing larger, maybe I

2:38want to just, I want to see if I can just

2:40make the

2:41calculation window larger, I can't seem to

2:43do that, so that's annoying, so what I'll

2:45do is I'll just

2:46I'll just have to sort of take the hit and

2:48make the whole thing larger, so that's fine

2:50.

2:50Let's start, so let's actually don't need

2:53to type the curly brackets, if you just

2:55type in partition

2:56tablet autocomplete for you, I prefer this

2:58because then I can actually structure the

3:00calculation in

3:00the correct way without making a mistake.

3:03So let's go back to the partition, I'll do

3:05this on a

3:05separate line, I don't like to do it as

3:08Tableau suggested, so I'll just type in

3:10customer name in

3:11this particular case and then at the end of

3:13this I'll actually put a colon because this

3:15is what we

3:16need to do to go to the next step of our

3:17function and the next step of our function

3:19we then need to

3:20use the order by function, so let's just

3:22bring that in order by, you can see it's

3:24right at the bottom,

3:25Tableau's calling out that we want to use

3:27that. Again I'll do exactly the same thing,

3:30I'll open

3:31up some space for it and for the order by

3:33function what we need to do is we need to

3:35tell it what we

3:35are going to order with, so we are going to

3:38order our sales, so this is our sales value

3:40, we are going

3:41to use that and we are going to order this,

3:43let's say descending, let's just mix things

3:45up, so it

3:46says ASC here, so DESC is the abbreviation

3:48for descending, it does come up there in

3:51autocomplete

3:52if you are not sure and so once we've done

3:54that we are actually going to define the

3:56number of tiles,

3:57essentially the number of groups to group

3:59these things by, so if I just type in end

4:01tile, you'll

4:02see that it comes up and then I can define

4:04the number here and in this one I think I'm

4:06going to

4:06use 5, actually not 15, 5 as a number, so

4:09you can see my calculation is indeed valid,

4:12let me just

4:13sort of break this down for you once again

4:15so you're absolutely clear what's going on.

4:17The first

4:17thing we're doing is we're defining our

4:19grouping, in this particular case we're

4:21defining our grouping

4:22using customer name, so what Tableau will

4:24do is we'll go find all our customers and

4:26essentially

4:26just save it as a list, once it's done that

4:29it's going to then order that the customer

4:32list by

4:32sales in descending order, that descending

4:35order is going to then define the direction

4:38of the table

4:39and it'll essentially put the customers in

4:41a specific alignment essentially, once that

4:44is

4:44done it will then run the entire function

4:46here, the entire function being the

4:48grouping function

4:49and essentially will create five equal

4:51groups in that data set, don't forget it's

4:54doing this on the

4:55customer name, so it's not doing it based

4:58on number of rows it's just doing it based

5:00on the

5:00customer name, so you've got to imagine in

5:02your head that we have one row per customer

5:05and then

5:05it's creating the groups, that's important

5:07for the next bit I'm about to show you, so

5:09now that it's

5:10done that we're pretty much good to go, let

5:11's clear the annotations and let's call this

5:13customer

5:14grouping and so our top 20% customers in

5:20this sort of file equal spreading of the

5:24customer names

5:25should all get the tile number one and so

5:27on and so forth and the worst ones should

5:29get tile number

5:30five, so this could be like a way of

5:33grouping customers if you wanted to, so let

5:35's hit save

5:36and you'll see that we get the new column

5:39over here, now the reason I said before

5:41that it applies

5:42it to the customer name not on a row by row

5:44basis is because you would think that if

5:46you spread out

5:47your customers in equal sort of way into

5:50five equal groups you'd think you'd get the

5:53same

5:53number of rows in each and you actually don

5:55't because of course the bigger spending

5:57customers

5:58tend to occupy more rows in your data and

6:00so you actually see here they represent a

6:02slightly bigger

6:03chunk than your smallest sort of group of

6:05customers, so this got me thinking

6:07initially

6:08in there I was looking at this saying this

6:10should all be equal but then I realized no

6:12it all depends

6:12on the grain or the level of granularity of

6:15your data so you need to understand that,

6:17check out my

6:17video on that for Tableau Desktop but

6:19nonetheless you can see that this is all

6:22there and if I click

6:23on one you can see it represents 22, the

6:25other one is 20, 20, 20 and then this last

6:29one is 18,

6:30so these got a fairly even spread it's

6:32almost like the binomial distribution where

6:34everyone in the

6:35middle is roughly the same and there's a

6:37tail end of people with tiny transaction

6:39and there's a sort

6:40of massive bump of people with most of the

6:42transaction value there, we can actually

6:45add an

6:45aggregate step just to sort of look at this

6:47in a bit more detail so let's go ahead and

6:50grab some

6:50values so the values that have been created

6:52here are going to be, where has it gone

6:54here,

6:55where did it go, disappeared on me, so

6:58delivery mode, dispatch, customer grouping,

7:01I think this

7:02is one, here we go, so we can actually

7:04bring the customer grouping fields, no that

7:06's country and

7:07region, I did I selected the wrong thing,

7:09let's try this again, customer grouping, we

7:11'll put that

7:11in here you'll see one, two, three, four,

7:14five, then we'll grab the sales values for

7:16these and

7:16we'll see that the grouping number one here

7:19has 20 million worth of sales, grouping

7:21number two,

7:22the next biggest group has five million,

7:24grouping number three has two million,

7:26grouping number four

7:27one million and grouping number five even

7:30less, it's sort of this nice stepped sort

7:32of grouping

7:33and you can sort of look at those

7:35transactions as a group over in tableau or

7:37something else,

7:38of course if I was to then sort of just add

7:41another clean step here and go back to the

7:43summary view you'd see this, let's just

7:46make this a summary view by going to the

7:48view state,

7:48selecting summary and you can actually see

7:50here that you do get five equal rows

7:52because of course

7:52there's only one line per row, I don't know

7:54why I went to this view but there's

7:55actually a lot more

7:56sort of granularity in the data there, I

7:58should have gone to another view and sort

8:00of just limited

8:01the number of fields but nonetheless you

8:03can see the tiling function working as

8:05expected,

8:05so this is going to be a nice quality of

8:07life improvement if you do need to group up

8:09your data

8:09in a specific way, it does need to be used

8:12in conjunction with the partition and the

8:14order by

8:15functions, these are sort of fairly

8:17straightforward functions to understand,

8:19what I'd say to you is

8:20really try and use them and see how they

8:23work, don't try and sort of confidently go

8:25where you

8:26haven't been before without really

8:27understanding what's going on, first use

8:29the partition then use

8:31the order by and really sort of test what

8:33your understanding is expecting versus what

8:36you see

8:36and once you do that you'll notice that you

8:38know level of granularity really does

8:40matter and also

8:41you'll start to see how you can use this in

8:43lots of interesting ways, the partition and

8:45order by

8:46functions in here are really really good,

8:47you could also use rank in this particular

8:49case

8:50rather than order by that's another way of

8:52working with it, so if I just replace this

8:53with rank

8:54and you'll see that this function still

8:57works, if I use that then you'll see that,

9:01actually the function doesn't work because

9:03let me just, actually let me check this, so

9:07I thought the function would work, so if I

9:09go to analytical we have rank, we have

9:11order by,

9:12and so that one is different I guess

9:15because you see this is why I hate this

9:19group of functions

9:20because I always forget, it doesn't matter

9:23how much I try, I always forget how exactly

9:26I'm

9:27supposed to use them because you would

9:29think that rank and order by would work in

9:31the sort of same

9:32way but you can see rank order by here can

9:34actually include a rank so that that makes

9:37no

9:38sense to me so you can even see here I've

9:40been confused by this, I went into a

9:42perfectly sort of

9:43fine calculation and I've made it worse

9:46actually by trying to use something that

9:49you can't use,

9:50so I'll leave it as is where it's working

9:51and we'll call the video there, thanks for

9:54watching

9:54I'll catch you in the next video.