Thank you so much for coming.

My name is Dennis Cao, and I'm absolutely thrilled to be talking about two of my favorite things in life, besides family and stuff like that.

Maps and Tableau.

But more specifically, creating maps in Tableau, or vice versa, using Tableau to create maps.

And so these are kind of one of my favorite things to do.

And I'm so happy to be here.

So thank you so much for attending.

Just a brief background.

I'm a social work professor at Carleton University, which is based in Ottawa, Ontario.

Originally from the States, originally just up north in Los Angeles.

I have the pleasure to be a Tableau visionary this year.

I'm also a public ambassador.

And then more specifically for this session, I have a graduate certificate in GIS, and

I've been doing GIS for about 15 years in regards to my research, which is around health equity issues.

And I also try to teach GIS mapping and things like that in my classes as well.

I first discovered Tableau about three and a half years ago, so I've been doing GIS for about 15 years.

But I only discovered Tableau about three and a half years ago.

And the rest is history.

And hopefully you'll get a sense of that today.

So for today's presentation, I decided to try to keep the agenda fairly simple.

I want to talk a little bit about maps, what they are, some general concepts, and design principles.

And then I wanted to talk a little bit about some of the things I think...

I spend a lot of time thinking about maps.

And so I think compared to the average Tableau user, I think I probably think a lot more about maps.

And so all these things I've tried to kind of wrap up and categorize into five broad tips.

Okay?

So next, after that, I want to try to apply those principles or those tips.

And so if you're interested in following along, you can access the data right here using that link or QR code and follow along.

Download it onto your desktop, then you can use it.

Like I'll be trying to...

I'll show you some things, but then you can play with the data.

And that's the fun part, right?

So let's talk about maps.

So by now, you've probably noticed that I love maps.

I use maps personally as well as professionally.

But I also love and enjoy the map-making process, kind of the thinking behind it and things like that.

And since discovering Tableau, I've been on a journey to explore the more creative side of map-making.

And so that's what I'm going to try to show you today.

And because I study and use them in my work, I probably think about maps a lot more.

And so hopefully you'll get a sense of that.

And when we do go into the Tableau and try to create a map, hopefully you'll kind of get some insight into some of my thinking around this.

So what are maps?

So here's a definition.

Maps are a symbolic, condensed representation of reality.

But the key takeaway from this, I think, is that maps aren't merely tools to help us find the nearest Starbucks or, in my case, the nearest In-N-Out Burger.

But maps are powerful tools of communication.

But more than that, throughout our history, maps often reflect the power.

Who has power?

Who was in power?

Who dictated the dominant values of society?

And I love this quote from Adam Schultz, who's a Canadian explorer.

Wouldn't that be a cool thing?

He's an explorer in this world, in this time and age?

And a writer.

And in his new book entitled A History of Canada in 10 Maps, in his intro he writes, maps are also a cultural artifact, a window into the past, a clue into understanding the worldview of the person or the persons who made it.

And so this resonates with me, because when you think about maps, just like when we create other data visualizations, bar charts, things like that, there are a million little decisions that often we have to make.

What to include, what not to include, what to highlight, what not to highlight, what to label, et cetera.

So it's important for us to really think intentionally about that.

So if there's a key takeaway, it's trying to think more intentionally about some of the decisions we make when we make maps.

For me, I think it's helpful to kind of think about maps in kind of two broad categories.

First, you have reference maps.

You know, Google is a good example of that.

Apple Maps is a good example of that.

And we often use that to navigate and find where things are.

The other one is thematic maps.

And this is an example of a map I created in Tableau, looking at changes in San Diego's black population between decades.

And this was based on the challenge to kind of mimic his creative data visualizations and using the colors that he used and things like that.

So reference maps, if you think about it, they provide an overview of a place.

They're not necessarily guided by a topic, right?

All features are supposedly equal and often include more detail than thematic maps.

On the other hand, thematic maps, you know, are often used to visualize a specific phenomenon or topic.

It's driven by some purpose.

And so you see an emphasis on specific features.

And generally, as a result, they tend to be less specific, have less detail, right?

And hopefully you can see some of the differences.

And then to me, the key difference is with reference maps, the story is reader driven.

They're going to look at the map and try to find the story that they're interested in.

Whereas in thematic maps, they're designer driven.

The designer is the one making the choices in terms of color and things like that.

And so as a result, there's a huge responsibility as we try to make some of those decisions.

And I think generally, most of our work involves thematic maps, I think.

Another thing to kind of think about in today's world, we're not necessarily talking about drawing maps by hand, you know, generally we're talking about digital maps.

And digital maps are composed of different layers.

So each representing a different feature.

And so this is a quick map, not quick, but a map that I created in Tableau Public, looking at multiple layers.

So for example, you have points to represent the bars in this area.

I mean, there's 73 that I counted, or a Google search, that seems kind of disturbing, right?

73 in the downtown area.

The second layer are the buildings.

So the bars are points.

The buildings are polygons.

And then the roads, which is the third layer, are lines, right?

And so we often work with what we call vector layers, which have distinct features.

And can be defined by points, lines, or polygons.

There's another type of data, rasters, but Tableau can't really handle those right now unless you kind of, there's some workarounds, but they're essentially grid cells or pixels with different values.

So if you look at weather maps, those are a good example of rasters.

And what's cool about this concept of layers, which is, you know, obviously in Tableau we have map layers, what's cool about that is now we can overlay different types of data, different topics, different types of features, as long as they're tied to some geography, and then explore the relationship between the two.

So here are some five basic cartographic design principles, and it's helpful for me to think about them as questions.

So as you're designing a map, right, do the map features and page elements contrast visually with each other and their background?

Okay, and in this map I try to visualize the downtown buildings very differently than the buildings around it, okay, to try to create that visual contrast.

Second, are the map's features, especially the most important ones, are they readable and easy to understand?

So this includes maybe labels as well.

Is the map or the most important thing on the most important map feature, is it visually separated?

Does it pop from the background?

And this is, again, my attempt to make it pop, the buildings in downtown, because I want this map specifically designed to showcase downtown San Diego.

Is there a clear hierarchy of the map elements arranged by their importance?

So when we think about labels, some labels might be bigger than others, and so in trying to do that, there might be a hierarchy created.

And then finally, are the map elements well balanced in the layout?

Okay, and so these are the questions I'd like you to kind of think about as we move forward.

So let's think about mapping in Tableau now, and these are kind of five tips, and I'm going to try to quickly go through this and then get to the mapping and then try to apply these.

So first tip, keep it simple.

This is a great quote by John Nelson, who works at Esri and is a pretty well-known map maker.

I'm not going to read the whole thing, but I just want you to take note of the highlighted text.

Specific phenomenon, pick a salient thing, leave everything else out, and exercise restraint.

And so when you think about mapping in Tableau, for those who have done it, you bring in a geographic field into the view, then you automatically see a background, background layers, and things like that, that's applied by Mapbox.

So the question is, do we need all of that?

And some of that might be noise, and so, or kind of make it a little harder for our story to come out.

So my own personal rule of thumb is really one map, one message, okay?

But if you have multiple stories to tell, and you're trying to do it in one map, you might be more effective creating multiple maps.

I lost my place in my notes.

So what does that mean?

That might mean one key feature per map, one colour palette per map, maybe one key symbol that you use to highlight a specific feature.

Things like that.

Second tip.

Do not accept defaults.

So like I said, when you plop in a geographic field into the view, there are a lot of defaults.

We see that when we do a bar chart, grid lines, things like that.

So when I plopped in San Diego, the city, something like this, all these background layers, ultimately we have to kind of revert back to what is the purpose of this map?

What are we trying to tell?

What story are we trying to tell?

What message are we trying to convey?

And do we need all of this stuff to convey that message?

Can we leave things out?

That's the kind of key thing.

And so question everything, right?

Question the defaults.

Question the symbols that are used.

Question the colours.

Question the background layers.

Do we need all of those?

Question the map options.

And we'll go through a few of those examples in the demo.

Kind of the counterpart to that is tip three.

Definitely sweat the little details, okay?

One of the things that cartographers spend an enormous amount of time on are labels.

The position of the labels around the dot or a shape, the size of the label, the font of the label, the font type, the font style, the font size, et cetera.

An enormous amount of time.

And so sweat the details.

So consider everything.

The positioning.

So this is a map of Balboa Park.

So I've supplied you with a few shape files.

Those are the shape files I used to create this map.

Consider the positioning.

Consider the inherent white space.

So we talk about white space, increasing white space to make things readable.

Geographies have a weird shape, right?

So if you notice, Balboa has kind of this weird shape where there's an open space, white space here, there's white space here.

And then everything is on this side.

And so this entire right side of Balboa Park, I thought about as white space.

So I was trying to take advantage of that white space.

And so kind of think about that.

Obviously, this is all floating.

And so I know there's two camps, right?

So I created this using just floating containers.

And so, you know, we can talk about that.

We can argue about that later, yeah.

And I tried to kind of balance it, take advantage of the white space, trying to position it in a way that made sense.

I spent an enormous amount of time playing with the size of the circles, trying to kind of figure out what worked best, right?

So sweating the little details is important.

Tip four.

So this was before my time.

But I heard that creating maps was a nightmare with dual access or trying to model the data in a way so all these different shape files were somehow linked to a single table, right?

With map layers, it's a game changer.

And I'll show you some examples.

Now we could just pile in the facial files, not worry about data modeling, and then overlay them on top of each other, right?

Which is cool.

And that makes a big difference.

Coming from someone who's done GIS, this mirrors more how I learned how to create maps.

Like by layering, not worrying about the data model necessarily, but as long as they're geographically linked in some way, we can overlay things on top of each other.

Okay?

It makes things a lot easier.

The second note I want to make here is a map is made out of multiple layers, right?

But layers are free.

So you can overlay a bunch of different layers on top of each other, even duplicate layers.

So for example, in this one I created, I tried to make the streets pop, and actually it's made up of three different layers of three different street layers, the same layer on top of each other.