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Hierarchies and other unique spatial visualization - Certified Flow Designer Training Session 3 transcript

Shared Flows

wow all right so I didn't get a chance to do as many

um analyzes as I wanted to but I didn't have a pretty good start on uh looking at the Airbnb Destiny density of

California's population centers so this is mostly going to look at the San Francisco area LA and then San Diego

down here um I've colored the each of these dots represents an actual Airbnb BNB location

and I've colored them by price so to get a better look at the price and

each area we can go ahead and go into the next slide and we can see that majority of them are down pretty low but

there are quite a bit that are pretty high up here so if you look at this one as an example um we can see this is in Beverly Hills

and it's 25 000 a night for that location so um that's quite a bit but um

but yeah if I just kind of Click around here you can kind of see that you know there's a bunch of different options and varying prices

um I can go up here to San Francisco huh um but yeah and then the great use of the

interaction and the uh um on selects uh overlay texts that

looks really really good yep and the next slide I wanted to look at

um that price versus the number of reviews and then the actual room type here so naturally we can see that

obviously the lower prices have a higher number of users there's maybe some more people that go there but it's kind of

interesting to see the as the price increases and we can see like where those different areas are at with

different room types so yeah fascinating um wow this is a great data set and

great visual um there's two comments I have um one is that for this visual on the

depth Axis or sorry the width axis for Price uh you do have the option for log log scale so for data like this it might

help reveal a bit more of what's going on sort of at the lower end uh

but I think that's amazing and then on the Second Step um if you want to jump over to that one

yeah um the one thing I noticed was the

the dots seemingly above the map a bit I'm not sure if that was intentional but I just wanted to make sure

um you as well as other people were aware of the button or where that setting is but you'll notice that by default it actually is like hovering

over just a little bit and if you click on the edit button which is that little pencil icon that will take you into edit

mode um is that little offset from map um it's right inside of charts uh yeah

right there so by default that's it's at 0.01 and if you set that to zero then

the dots will basically be on the the map itself okay and so so anyway it's

just like it's less about uh critiquing you and more for everyone else's edification

um in case they've encountered somewhat of the same uh four Maps yeah I didn't notice that and I wasn't sure how to fix

it so I appreciate that thank you yeah of course and then one last sort of uh and this is my personal uh design take

is that for the connections themselves here if you select the um connections

that um whenever you have a lot of density um like this

um one bar will sometimes obfuscate others and so you can change the opacity of the color here

um I do something more like 60 or 70 um I mean there's sort of anything's available but the uh it's in the colors

section um and that opacity will essentially allow you to see through a bit of the

this the uh the connections and so it just makes it a little easier to sort of

navigate and see and but that's just a personal design preference since um

takes um really awesome presentation cool thank you yeah that's great did you

get the map off our of our help center yep so the the map of California came

from your uh your U.S states

Google Drive yep great yeah very nice

thank you right anyone else like to present

oh girl all right go ahead how so I um this is uh really quick because uh I

after last time uh the presentation uh Bill did uh I think that was a really

good way to learn how to create a present uh visualize uh uh Geographic

data so I just replicated it in front of my students to give them an example of

this and uh so I expended a little bit um you know just to for the homework uh

let me see how do I share my screen I want to share screen uh Google Chrome

um share sent

okay um so this is uh uh basically what oh

can you see this yes okay so so this is uh what bill

created uh during the last last weeks uh basically 10 000 cities and uh it was

uh the photograph I think for the color of the map and uh I went a step further

uh was this to kind of aggregate um the population of cities into each

for each country so obviously China would have the largest population city population uh so each country would have

their own uh one dot per country like you know like this so and then I went

one more step to look at it based on um you know

um different continents so it's the casino of Asia as the most population Oceana

New Zealand Australia has the um least population of city in cities

that's it okay and these are the continents that the 10 000 cities

um exist on yes so there's ten thousand dots on that graphic

uh uh yo I I created a snapshot so this

is population by I aggregated uh okay yeah

so that was uh yeah my next question is if you did aggregation in the tool or outside and it sounds like you used the

tool to create a snapshot which is great because we're actually going to cover that a bit today um in the snapshot so that's uh really

cool that you you did that um it was quite easy to do it just uh you drag a a column up to the on the

title bar and it just does it for you yeah yeah absolutely um

yeah I'll I'll show something in just a moment here that is related to that um but before we do that any other

commentary for anyone else that would like to present yeah I just wanted to say we love it when people take these

flows that we put out there and extend them and make them uh more comprehensive

or give a Different Twist to it nice going

um I'd like to present mine that's okay yeah go ahead Henry okay uh we'll get it

up this is from a data set that um I'm a

big fan of it's the exoplanet data from NASA um so to start out with the field like

all these dots represent a star that we have found uh planets orbiting around

um you move forward and they all congregate onto the globe and this is all the locations of the observatories

uh that actually were responsible for finding these exoplanets uh then we move

on to the next one and this is all the locations of the exoplanets in the sky

around us so like if you look up at the sky from Earth depending on where you are around the Sun like this is the

globe around our solar system that we have found exoplanets from and then the

next step uh it actually has distance data so uh now all of the dots are

actually arranged via the number of light years they are away

um from our location so um that's that's what I have so far I

have a couple other charts that I'm still working on uh this one's pretty good this is all of the uh single

location stars that we found um or the observatories that have found them uh Kepler which is a Space

Telescope is way ahead of everybody else still uh so that's and uh so that's that

it's it's kind of difficult because the Kepler bar is so large I need to find a way to like get it in screen and still

everybody else and then um and then this one I just started working on the other

night this is all or this is is the um kind of breakdown of the stars and how

many planets they have around them so like the larger circle is the ones we've confirmed one planet and then I believe

it goes all the way up to eight currently we found one start with eight planets around it so uh that is that's

something I'm going to continue working on I was actually working on it before this class started but wow it's a really

fun data set and it's always growing too which is super fun yeah yeah where'd you get that data set

um just search for like NASA exoplanets they have a great page with so much information that's the best part about

government agencies they just put everything out there so wow

that is incredible um yeah that was really really awesome uh both from a Content perspective but

also the visuals the uh the colors at the end I noticed a few red as well there's uh green and red

does that have any meaning that that did I have already forgotten what it was though okay okay um how did I do that

that was oh that's the that was the planet numbers I don't know that's the size the oh the colors were the system

distance that's right um yeah it goes from like 1.3 light years like 8 500 or something like that

and um if I recall correctly the visual where you had the the dis like the

exoplanets a set distance away you actually still use the map function to

set those distances right so I think what's I love this one where it really extends the idea of like what is the the

um a map here where it's a map of the Earth but now we're taking it and using those distance measurements to share

something uh as more of like in space as opposed to a dimension of like

population like household so um I love the different ways Maps can be used here we've seen quite a different quite a few

here but I love that Visual and I don't know what you're thinking for that last one if you're thinking of like a pyramid

look um that might be cool yeah but uh right now I think they're overlapping and and the one little button I'll just hint

towards because you might um encounter it um or it's it's sometimes a little

tricky to find is within additional Dimensions there's a little field called Direction and it basically says in what

way does it disperse vertically horizontal or through the depth Dimension okay so I'll just point you to

that play with that and that might help help on that last step but uh okay yeah

that was awesome that was awesome guys those are amazing presentations from

everybody uh just kind of Blown Away uh with the start of this so you guys are

starting the bar high for me to dive into hierarchies and so um I'm a little nervous but that was

really cool um and if you guys are open to it I would love to start um sharing these with other with more of

a larger population so we can talk separately or I'll probably email separately uh Jessica's uh take on that

but uh to be able to amplify and and showcase some of these I think would be well worth it
Diving into Hierarchies

um so for today we're diving into hierarchies um and specifically the one we are going

to dive into together um actually close this one is related to

creating a balance sheet um and so I point to a balance sheet because it's sort of a very easy way to

think of a hierarchy relationship um but in a way that you don't typically
Balance Sheet on Hierarchy

see a balance sheet shown um and so here we have assets and liabilities and shareholders or

stockholders equity which should always be equal to each other that's why it's a balance sheet that the number of assets

should equal number of assets Plus or liabilities plus shareholders equity and

So within each of these this first view you can see sort of the the big picture in some sense the

um the hey Mike a full span here yes can you go full screen yeah is it um let me I just have you in

your in your uh box sorry okay yeah let me uh I'll present

this way because I know the text is a little um yeah thank you small here but um yeah

and so each of these outer components is uh one of the line items So Good Will

um sort of the the list goes through and this uh company is actually T-Mobile um if I go more to the side here and uh

we'll play around with some of the the ways to to visualize this and rotate it but

um I thought some of the interesting aspects uh to this um one were the the really large values

here on the asset side was Spectrum licenses so 82 billion dollars worth of spectrum

licenses so the license for that area of spectrum that they own is by far their

their largest assets um and where was the other one

I can't remember the other one was or what the other Insight was um I guess long-term debt but that's not too surprising but anyways um what

you'll notice here is one there's somewhat of a snakey design here where we're using

um lines or area charts to connect these data points together the height here is

equivalent to the dollar amount so it's essentially a bar graph on one angle but

it's also a hierarchy showing the relationship back to the the center and so we'll show this through a variety

difference means but you can also show this not just in a circle but also

vertically here and this might be a little easier to to see and understand

um and I can actually rotate this as well um oops

yeah wrote this is 90 degrees and that also sometimes aids with understandability

um so we'll go through basically the the creation of these um and one thing I'm just going to note is that it's a little

more technical but I think we'll uh in the process learn quite a lot around how
Fixing a Flow in an Error State

to actually um and it looks like this might have gone into an error state so

if your flow ever gets into a state where something doesn't look right I recommend refreshing the page

or save and refresh and that is typically an artifact of the preview window this is a preview window of the

presentation um and that then when you go through playback um it's a it runs the script again but

it's anyways sometimes you can get into a state where the preview window is not accurately reflecting what the

presentation view will look like so that does happen on occasion so anyways that's the the visual that

we're going to go through and start to to create and so this can be applied to a balance sheet a cash flow statement an

income statements a hierarchy of information and even to our points of of being able to show all the different

areas of flow so still sort of a work in progress and a little large but these

are something bill and I have been working through these are all the top level areas uh that we are covering the

flow homepage you guys have gotten very familiar with most of our work here together has been within swarms and

different components of swarms will probably very quickly go through quite a lot of these other groups for images

texts and models and sort of things just to check the box but we'll hopefully get

be able to share this out with you guys and we're marking down what we've gone through already what we have yet to go

through that way you can sort of see the the whole Gambit of of what is available
Nuances of Labels

the one thing to note and something I will acknowledge that we are still working through is labels have a lot of

nuance to them you'll notice that the labels here are radial in in pattern

where they radiate outwards um aiding in their ability to be deciphered but there are some issues

like right here that you know is just because of the crowding of information

um in that x-rap might be on so we'll cover some of the edge cases of what we're working through um but uh but how we think this is going

to be unlocked is with templates which are coming out soon where we're not

coming out soon but is something I think you guys will be more heavily involved in where after creating some a flow like

this like a hierarchy that is more detailed that we can save it as a template that then allows anyone to

upload data that has a similar format to reuse basically the perspectives and the

colors and and some of the other characteristics but with the different data sets to help someone get going

because as you'll find out your original you'll see here there's a few components to building one of these that's

important for for us to know as as sort of the core designers here um but we'll note that they will get

easier with templates so with that let me actually start to dive in

um and so for this first let me reference how you can actually get to this data so once again going to our

data Library we will be using a training data set for T-Mobile

so this is within your demo media and assets folder which I'll Place into the

chat window again um on the chat window

here we go and

oh and Mickey I just saw your message sorry um I'm so sorry we skipped over you if we have some time at the end

let's make sure to have you presents um um yeah let me finish this thought but

uh we definitely won't don't want to miss your presentation so apologies for that okay so let me go back here

um yes so I put that into the chat window so this is going to be inside of training data sets

um and we have T-Mobile financial statements and we have it saved as a Google sheet so that everyone can

basically look at this data first as well as we're going to use this to import in to look at a few things so

essentially what we have here is each of these is the line item on a cash flow or on on these reports and that each of

these can be categorized into a larger category and then a subcategory and then the details for for each as well as we

have this information both for the year 2020 as well as 2019. we have the dollar

amount here in millions and then I've actually gone ahead and multiplied it out by a million to show the real value

here since when we have the auto rounding inside of our our system

um it's uh it reads this still is 82 000 um as opposed to 82

um a trillion or billion um so anyways is there any particular way that

you're organizing that in terms of you know top down
Long Dataset vs. Wide

yeah so the most important thing is that this is a long data set rather than

locked and wide and what I mean by that is that you could very much very easily also see this information depicted this

way where you have 2020 as one column and you have 2019 as a separate column and that's totally fine you could

actually do it that way just recognize that 2020 will need to be its own swarm

and 2019 will be its own swarm and if you wanted to combine the two in either

uh hierarchy or to show something over time that it needs to be in its own

column and so that process is called unpivoting and if we get more into the

data transformation that's a whole whole bag of worms that is a little outside of

the scope for what we're going to be covering um but definitely is is somewhat necessary here but how you actually get

this to this data is kind of cool I think is you can actually get this from the SEC website so if you go in to the

SEC go to filings you can go into Edgar and actually search search for a company

or fun name so we can type in T-Mobile here

and once we open that up we can open up the 10K and we'll see the 10 cues make sure to

click on the 10K and specifically open the filing that was made then then click

on interactive data I know there's a lot of like clicks here so interactive data

and then there's a little button that says view Excel documents I think it's kind of hidden with your system but uh

that's okay because at the end of the day you get a pretty impressive or you get a document that contains

pretty much everything you need um so here we have the the data and we

have all of this on different tabs and basically we can use this balance sheets
Column for Category

uh to take what is current liabilities and what we would do is actually add

over to it so that we have a column for category

so this would be assets and then I'll create another call or one

called subcategory and this is current assets

and so what you're seeing me do is essentially categorize all of these

um and I will not include the totals so we would not include the totals here since we don't want that to be part of

the aggregation but I do the same thing for liabilities

and I'm just going to skip ahead here um the there's also long-term liability

it's not just currents but I'm sort of skipping that categorization since we

already have the data I just wanted you to know where you can get it because you could do this for any balance sheets and

lots of information so now that we have that downloaded

um what we'll do is copy over this URL and on inside of flow we are going to

click on select slash upload the loader type we're going to do Google spreadsheets and paste in this link and
Importing the Data

when we import we will import that data that data in

and we will then very quickly click on edit slash re-upload in the future there

will be a button called Data transformation that will take you basically to the same spot and the thing

we're going to focus in on is snapshots um because this is where we are adding the categorization or the the creation

of the hierarchy by creating groups so there's little row groups here and how sort of mentioned it last earlier but

essentially what you do is you drag and drop up to this little section that says drag here to set row groups and so I

want to drag them in order so I want to have category on top and then I want subcategory beneath that and So within

this you'll see that there's been updates already so we can see assets here and if I click the the carrots I

can see that there's other assets and current assets and I can explore each line item so I've already grouped things
Value Aggregations

together and then I can perform aggregations so I can take the real value and go to

Value aggregation sum so now I'm summing up each of these line items so that at

the next level you're seeing the additional amount and so I'm going to do

that here for Value as well

and I'll skip through sort of the other ones um you know one other one we might do

here maybe just for category no Optical leave it like that actually

um and the most important thing to do is to click this great snapshot button so I have to set it up you want to make

sure to take that snapshot of the information and so the now that is saved in that manner
Sorting a Column (Ascend or Descend)

um the other thing you can do as well as sorts so just by clicking on a column you'll sort it up ascending or

descending and that's does impact the visualization and the order in which the

uh columns appear so from here we've created a snapshot

and so if I close this snapshot is right below data source

because there can only be one snapshot per swarm you can't you can create multiple snapshots but

um you can only have one snapshot per swarm so that snapshot carries through to the different steps and I didn't

cover this in the morning session yesterday and I I realize I should have but I want to just call out sort of how

this is structured by showing it first in a scatter plot and then we'll jump into uh hiring so the first thing to
Hierarchy level

know is that there's some automatically created Fields called hierarchy level

which is basically one two three um based on where it is on this uh in

this data set where we have three levels the the top level the the sub subcategory and then the actual line

item um and so um on the Heights I'm just gonna put

um I guess value sure that'll be fine now the depth axis I will put a hierarchy

group okay so hopefully this will start to make sense

um in just a just a moment here uh if you bear with me so basically there's

three levels of the hierarchy and uh maybe it's just to call out that there's a field called hierarchy level I'm

actually just going to switch back over to to hierarchy because that's actually how you typically create these all right

so this is hierarchy um and it by default starts with a circular layout you can switch that to a

linear layout which I think let's just start with here and then we'll switch to Circular in a moment

um and so this is level one this little dot here on the always left level two is the middle and level three is this third

one and that relates to the data um where if I go to snapshot one this is

level one uh level two and then level three is actually each line item so each each actual line item there so I do not

need to bring in detail up into the grouping um it's not necessary for to

add the actual line item um onto the hierarchy okay so from this uh we might want to

add some colors um so we could do this in a number of ways one thing we could do is do a color

scheme um based on let's do this based on category okay this is

actually a good example of where you might get confused and let me just clear this up a little bit so

you'll notice that we see the first and the last levels but are missing level

two and we selected category and if I select subcategory we'll see level two but are missing level one because what

we're trying to do is apply a color scheme based on the data that is contained there based in based on the

subcategory here and okay and so

um if you look at the snapshots you'll notice that um for category there is no category

listed at this top level for assets or current assets um

um yeah and and so the way to remedy this is to have these filled in and so

we can do that by going to Value aggregation first um and a little bit of a uh yeah

something to a small detail here it's a easy to miss but

um but yeah is something that's you might encounter and so now essentially we are coloring this based on the first

one it sees as opposed to being actual representative of what subcategories are

really there so it is somewhat forcing it's as opposed to being uh truly

correct so I don't know if that all makes sense to everybody but I sort of want to call it out um as one way to uh to do this

okay so to help you understand what's there let's add some labels so on this

snapshot or on this swarm we're going to click on new labels and the first thing we'll do is click on hierarchy group and

hierarchy group basically takes all of the hierarchy levels that are not the last node level and adds the name to

them so this is whatever was grouped on so here we have assets on the bottom we have liabilities and general Equity up

on top um and if I want to put labels on the Node

level that I need to create another label object and I can do that by duplicating this or if I go back to the

Swarm I can also click on new labels again and this will create another labels asset and on this label I want to

bring in the item which is the very it will only exist at the node level since

item does not appear at the at the upper levels and so you'll notice that the

text is all running into each other and a bit difficult to read so what we'll want to do is first turn off wrapping

this will make it so the text does not wrap to a new line and then in addition

we might want to reposition this information so we will want it left sent

left of the dot and be on the center of the dots and

um this I believe might be an instance where I just need to save and refresh um so let me go ahead and save control s

and if I refresh um there might be something just going on with the preview window for labels

which I've mentioned have have a little bit of uh stuff going on so yeah you'll

see that the the font or the the labels are now resolved

um and I'll space these out just a little bit by adding some Heights just to call out sort of these little

components that you can start to Intuit these uh account for the

um measurements of the size of the this hierarchy um both in width and Heights and this is

controlling where you're placing the spacing of of this information

um so the last thing to do here is to add in some connections so what we're going to do is actually add connections

based on I'm sorry we're going to click on connections based on hierarchy level

so it's a little drop down based on hierarchy level and that will create the connections based on those hierarchies

that we assigned now this is sort of uh I think pretty interesting and uh

putting more more typical for 2D view um you know there might be more you'd

want to do for some of these labels some some sort of Tricks here are are to bring it out a little bit so that it

stands in front and you can also add a background so if it is obfuscated that

you can make it a little more clear to to read through by adding in backgrounds

um but the the thing I wanted to really highlight here is I will add another step is that in three dimensions you can

actually use the height so here what we're going to use for Heights is that aggregated

um and actually I'll use just regular value in this instance but now you'll

notice that the dots are offset based on their aggregated real value

and the thing that we've been sort of uh encouraged people to do is to create an

area chart from this so if I click on new area charts an area chart is a

little different than the connections back to the

axis in that it fills in between data points as well I mean somewhat of like a

Sankey kind of way where you're seeing the distribution I'm going to alter the

size of this just a little bit here to make it a little less tall so you can more easily see

things and the one thing you might also want to do from this is rotate it so if I rotate

this minus 45 degrees along the width axis makes it just a

little bit easier to see some of that depth now the reason I'm not going all the way to minus 90 degrees

is that's at least for looking at it straight on the texts sometimes are

overlaying each other so we could have a whole lesson just on labels and and formatting and stuff like that and we

might but I think what we'll mostly find is that by nepotizing these and putting

them into formats that really we know work that should solve for the majority of cases so that's sort of what we're

banking on a bit more and I think you guys are going to be more critical to that as well as some ability to interact

with this we won't uh have you guys do it but we have just briefly show we have a node

editor which allows you to create a very complex interactions where if I click on a DOT

here it will cause other things to occur based on whatever I set up in the node editor that's for a totally different

topic and I'm not going to cover that but just sort of highlighting that that will be a part of hierarchies so you

know last but not least here just to show how we can transform from one visual to another if I change this from

linear to Circular you'll see that the the switch is pretty much automatic and

that's uh yeah I can sort of go from there the one thing I wanted to call out

for radial text or sorry for um for these types of graphs that are

circular is that this works fine when you're at an angle here

um of like you know 90 degrees or something where you can still read everything

um but that you might especially if you get into more of like a 355 or or a full

circle that you want the text to radiate outwards and so to accommodate that what

I'll do here is on um this last line for label two let me

duplicate this and I'll turn off the first one and on the second one I'm going to click this little radio button

and I will also click enable rotation and it looks better but it still looks bad the reason it looks bad is because

anytime you use radial these radial buttons that you need to set the

position center Center Center and then you'll be at the right spot and so now these are more easy to read and still

face you as you rotate around the object and there's more we could do like I

mentioned but I will sort of pause there so I know I've covered quite a bit here with hierarchies as well as the root of

hierarchies which is snapshots and snapshots can be used both for that

aggregation buts and I realized this after the fact here I actually

aggregated everything for 2020 and 21. it's uh the reason being is that in that

snapshot one year 2020 and 2019 are both

there and so I actually want to filter this I mean neglected to do that and so I can easily do that here if I go into

here and just type in 2020 or sorry let's click the filters of

equals 2020. and so now this data set is only just 2020. and

um I clicked I was doing that to the raw data State set here as opposed to

snapshot so just a note to be on the right view so to be on Snapshot here and

then I want to filter this only look at year 2020. so now we'll update that snapshot

and that should Ripple through to then update all of these visuals and those

interactions so uh sorry about that but I'm glad you guys get to see sort of

this in action um so let me pause there to see what questions you have and what I can

elaborate on

Michael what other than financial data what else have you found this useful for

yeah so um we also have seen it use um

trying to think here we've seen it used in an m a transaction

whereas basically an org structure like here's one whole business unit as well

as the geographies so it was basically like Finance you know like where does Finance it or like sorry the like an

employee layouts um or um uh interactive org chart yeah interactive org chart

that's yeah a good framing um and that actually reminds me um and this is what I wanted to do quickly with

um um uh the information that have showed because this is kind of an interesting
Maps and Hierarchies

use of both Maps plus hierarchies um so if I just create a flow here

quickly and select from that's 10 000 cities data sets

um so just from that uh sample data sets 10 000 cities that I can create a

snapshot here that looks at um let's do

we'll just do country um for now there's far more that you could do here

um and actually I'll put consonant too so we'll have uh country and consonants uh update that snapshot and so now if I

select that snapshots and add a map and actually place these dots on the map

so if I do this based on coordinates using map one and I'll

select latitude and longitude that will work

um but the one thing I neglected to do here and is sort of the the interesting

way to show this is that we can aggregate this latitude and longitude

um based on averaging so if I average these I inevitably find sort of the uh

the the center the geographic center um for the most further SMH cases um for

each of these and so what you can do is in this snapshot if I change this to a

color scheme based on hierarchy level um and just for this I'll also add in

some additional Dimensions height based on those hierarchy levels um and I'm going to invert it so three

one um so if I do

0.25 to zero this is the height off the map and I can

actually go in still to add in connections and add in based on

hierarchy level and I'll make the transparency of this more like 40. but
Structures aggregating info

you can start to create these structures now which are aggregating information

and it's placing at a distance off the map based on something you're aggregating so the better thing to to

aggregate is something like population or something like that but now you're seeing the middle of each of them so

this is kind of one of those things where it's a combo of the two it's a both a hierarchy but it's also geospatial and I think that has a lot of

Promise as well for being able to show aggregations so still a lot more to

explore I think in aggregations as well as the ability to interact but um we'll be very curious to see if you guys have

other ideas on what you'd like to see that is sort of um somewhat relationship relational data

it's a little different than a graph database that's for sure um could you label that Center Point

that is the source of the hierarchy uh you can great question

um the um the only way to do that is to really add in a value that is a dummy value

um so if I go into this snapshot basically I need a something up on top
Type in a Snapshot

here um and so I know this data set already and that I have something called type

which is balance sheet for every line and so if I put type balance sheet

that will actually now be the the top level and so now I'll see sort of a root node

in the very center now it's not quite accurate because this is adding the two together

which um doesn't really work but um anyways I just wanted to quickly show

you where you could do that so you can you could put labels on the countries

there at the top of those pyramids yes sir right yes yeah so labels here

definitely um yes

yeah that's powerful thanks um and so here I'm selecting country is the label but I actually only want to

label when it's when the column hierarchy level

is greater than or sorry is less than in this case three

because I don't want it to show up on the dot level but I do want it to show up here on the the country level

um and so um the other thing here is this is radial and I want it to basically

uh be further away

and that almost worked okay sorry I'm diving a little too deep into some more

experimental to your stuff but um but yeah I think that's an interesting sort of uh

use of hierarchies that is a little bit more emerging it's a pretty common use

case to label the highest level and maybe the second highest level in these

hierarchies and not label the details just because there's so many of them

all right what other questions do you guys have

okay I know it ran a bit over um so I appreciate you guys sticking on here

um I think the uh that was really awesome this was probably one of my favorite days to see you guys presents

uh those are really awesome um and yeah if you guys want to create some AR videos with those or anything like that

um I would be totally game to to do private sessions for you guys to to help record those or whatever

um I think that's awesome um so really inspiring to see and we're available here to help you homework is

very similar here um where it's basically you know find some hierarchy data well we can point you to this data sets or even you could

reuse the 10 000 cities like we just showed um but you know practicing there and you'll probably run into a few more

things to ask about I'd say um so I appreciate your sort of uh

uh kindness or understanding um while we we

still make some hierarchy updates Hey Mickey hey Michael I had one question do you

think next week we could cover how to potentially animate through data that

has a Time access yeah great Point let me take a note

yeah animation is a pretty important aspect um the really short answer is in today's

platform the way we do that is to create two steps first step and then second step and the first step you just apply

filters to the date and so it ripples in through that time and there's actually other

ways to do it too which we we might cover as well um but that's sort of the simplest way

and that the other thing to just quickly note because I I think is really powerful and use it a lot is

um in-step details you can control the amount of time it takes to go from one

step to another um and so um I'll just

you know just put this into random perhaps and turn off connections so if I

were to to do this as a movement to have dots then I could quickly change the

amount of time this takes you know if I make it like 30 seconds it's going to be way more dramatic and slower moving than

if I were to make it two seconds which is the default so just something to be

aware of and uh yeah know how you can sort of use that and there are some

other details within this just so you're aware there's a little animation Tab and there's some some details here for

ripple duration and item duration um yeah which we might get into uh it's

yeah might get into you but because uh last week in Bill's presentation he showed how the data dots splashed out to

the various regions of the map and I was like snagging so uh even if it doesn't happen

in the class I know it's capable of some really fascinating stuff like that so yeah we can get an idea about how to

inter interact with the timeline that would be a real uh yeah animation is one of my favorite

parts of the product actually for for dramatic presentation so that that will be fun to present that

next week all right uh other questions otherwise

Nikki I do want to give you the floor if you do want to present no I figured what I learned today about hierarchies would

help me with some problems I was having so I'm out okay perfectly content to present next time okay okay sounds good

then we'll do that um cool any other questions or comments

otherwise we will close up for the day I just have one comment that I end up uh closing out most of these sessions with

and that is if you are stuck or if you think there must be an easier way or a better way reach out to us with a

question we've got a lot of it a lot of tips we can that we can provide to you

so there's no such thing as a silly question in this in this in this space so we're happy to help

and to the question of getting getting this flow um this will actually a good way to uh

quickly uh point to one thing um so a few things in the share dialogue

there's a little button called share and you can create a public link so when

I click that button for uh creating a shareable link this you link is like a

of it if they want to use it used for their own or to remix basically you can

also share it privately where you can put someone's email or if you ever have a question for any of us you might be

familiar put in Michael at flow or Bill at flow or industry or Json app flow and

then it will be sent directly to us and then for some Enterprise accounts we have organizations and some other ways

to to share um but just sharing the ways you can share but the last thing I wanted to

show was Discovery so this is not used a ton yet but um we're hoping more will is that when

you click on publish for Discovery there is a tab on the Lister called Discovery

so if anyone wants to publish there you can't so you can take any of the flows

that you have created and publish for Discovery and then we can see them too

and uh we'll occasionally bring over some into the featured tab but that

mostly is Monitor or managed by us and the Discover tab is sort of open to everybody so you'll notice there is one

there called bound sheet from training and that is today so you can use that as sort of a a reference points or

um for learning on your own okay

great all right well thank you guys so much for your attention and amazing

presentations uh really exciting to see the progress and look forward to next week thanks everybody

bye-bye everybody thank you thank you thank you thank you bye thank you