Episode 47: Charts Can Lie, But Here’s How You Remain Vigilant - Featuring Alberto Cairo

Welcome to episode 47 of Data Viz Today. It’s no secret that some charts lie. You might be thinking that only a subset of people who maliciously create a chart to serve their interests are guilty of this, but the truth is, there are many ways in which a chart can lie. You can make a mistake in your design, or use data that’s insufficient, or make conclusions that aren’t accurate. I’m guilty of this, and guess what… so is Alberto Cairo! He wrote a whole book on How Charts Lie based on his experience creating and reading charts.

In this episode, I finally got to ask Alberto’s opinion on some burning questions that I have, like how he personally reads charts to assess their quality, how he’d structure a graphics team today to make sure they create quality graphics, and where he thinks we’ll be fighting misinformation in the coming years. Most importantly, he explains why we shouldn’t throw up our hands and give up on charts even when some mislead us.

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.


Allison Torbancairo, book
Episode 46: 3 Smart Tips for Building Your Portfolio - Featuring Dillon Winspear from Designed Today

Welcome to episode 46 of Data Viz Today. Are you struggling with putting together an effective portfolio? I find it hard to know if I'm using my time efficiently. What do I need to include? When is it enough?!?

In this episode, Dillon Winspear is here to help. He's reviewed hundreds of portfolios as a Senior UX Lead at Domo, and I asked for his top tips for building a portfolio. Listen in and learn how to impress your hiring manager even if you only have 10 minutes to spare!

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

Dillon’s podcast Designed Today

Dillon’s podcast Designed Today




Episode 45: How to Use Data Viz to Bring People Together and Feel Connected - Featuring Amy Cesal and Zander Furnas

Welcome to episode 45 of Data Viz Today. Visualization isn't always about revealing the patterns in our data. Sometimes it can be used to bring people together. This featured viz is a project by Amy Cesal and her now-husband Zander Furnas that they created for their wedding to connect their guests to them and each other.

In this episode, we'll hear how this project was created, what they’d do differently in retrospect, and what specific questions you need to ask yourself before you start designing data viz to connect people.

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

In today’s episode, we’re exploring how to use data viz to connect people. The featured viz is a project by Amy Cesal and her now husband Zander Furnas that they created for their wedding. They created personalized badges and a giant network graph of their guests printed on a fabric banner to help bring a unique aspect of their relationship to their wedding (since they met while collaborating on data viz), and to help their guests feel valued and connected. It also acted as the perfect conversation starter.

But they learned that when you’re creating data viz to connect people, you have to always consider that the data as actual people…not just numbers in a spreadsheet... 

So let’s hear how this project was born, what they’d do differently in retrospect, and what specific questions you need to ask yourself before you start designing data viz to connect people...



Katherine’s inspired viz: a prototype of an attendee badge of a local Women Who Code event…

Katherine Mello’s  Inspired viz

Katherine Mello’s Inspired viz


Episode 44: 3 Steps to Find & Strengthen Your Biggest Data Literacy Weakness - Featuring Ben Jones of Data Literacy LLC

Welcome to episode 44 of Data Viz Today. Data Literacy is on everyone’s mind right now, but it always seemed like a nebulous topic to me. What is it exactly? How can you tell how literate you are? More importantly, how do you improve?!

In this episode, we’ll learn why you need to assess yourself, no matter how literate you are, and how to identify the next step you need to take to improve on your weak spots today.

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

Episode 43: How to Visualize Paths Through Time with a Narrative Chart - Featuring Sahil Chinoy and Jessia Ma

Welcome to episode 43 of Data Viz Today. Every day, events are happening and people are moving through time making decisions. How do we visualize that? How do we visualize that for hundreds of people in a way that still makes sense? Even more challenging, how do we humanize that visualization?

In this episode, we’ll learn how Sahil Chinoy and Jessia Ma from the New York Times solved this problem by combing hundreds of paths into a narrative chart.

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

Welcome! I'm Alli Torban.

  • Every day, events are happening, people are moving through time, making decisions… How do we visualize that? How do we visualize that for hundreds of people in a way that still makes sense? Even more challenging, how do we humanize that visualization? Today, we’ll find out…

  • If you visualize data for a living, you’ve probably run up against the challenge of visualizing a lot of events happening over time, or people moving through time making different decisions. At first glance, I’d probably think of using a network type graph - with people or events as nodes, and the relationship between those things are represented with connecting lines. Or maybe try an alluvial diagram, where people are grouped a certain way and then regrouped a different way. Like how many congresspeople are democrat or republican, and then how do those groups break apart when grouped by the type of undergrad school they went to (like public or private college). This seems like a very natural way to show paths through time, but everyone’s grouped together. Once the people get redistributed into different groups, you lose sight of where the people were groups a few steps ago.

  • This is the very problem that Sahil Chinoy and Jessia Ma - both graphics editors for the New York Times - set out to solve with their graphic called “How Every Member Got to Congress”. So in this episode, we’ll hear how Sahil and Jessia visualized 435 paths through time in the most beautiful and captivating way.

  • About a year ago, Sahil was poking around the official congressional biographies, and noticed something interesting… so many legislators cited very similar experiences before being elected to the House. But how could he show all the individual paths while also showing how these legislators were following similar paths? First he needed to get all the data…

  • He scraped the bio guide, but noticed that it wasn’t comprehensive - everyone’s path wasn’t completely fleshed out, so he had to supplement it with other data sources. It was a really manual process and he ended up with a huge google spreadsheet that was color-coded so they could fact-check the 435 legislator’s paths line-by-line. He sketched out how he thought this chart should look but thought it looked way too crazy, so he scrapped it. But a few months later he made a prototype with d3 which looked like pie charts connected with hundreds of lines, and without much hope, he sent it over to his colleague Jessia with the note “a wacky chart”...but she saw something in it...a sliver of hope that it could be transformed into something comprehensible…

  • Jessia was asked to detangle this mess, and first she asked herself, “what’s the newest and most important information here and how can I bring it to the surface immediately for the viewer?” She said there were two visualizations that had the same spirit of this data - Minard’s famous Retreat From Moscow - I think it’s a compelling example of showing a path through time with extra information, and Periscopic’s One Angry Bird, which is a beautiful example of using very organic lines to represent data. So Jessia grabbed her comb and began manually tweaking Sahil’s graphic in D3.

Sahil’s early prototype.

Sahil’s early prototype.

  • Sahil had created many invisible nodes that helped separate the paths of the congresspeople so Jessia could more easily pull the lines out and around so the reader can more easily follow the trends. Jessia discovered that being intimately knowledgeable with the dataset was the only way that she could have the appropriate sense of space to know the best way to arrange the nodes and lines. It took a LOT of work and it was a couple of months of work between the time Sahil created the prototype and the final graphic was complete.

  • But the hardest part of this graphic? Keeping the faith. Sahil said there were so many times they were close to scrapping the idea because it just seemed like too much to detangle. Maybe it was too ambitious and a series of bar charts would make more sense. Their editor disagreed. He encouraged them to keep going and to trust that readers would understand and appreciate this non-traditional chart. And he was right…

  • January 2019, they released their finely groomed baby in the New York Times Opinion section called “How Every Member Got to Congress”. It flows from left to right, 435 lines starting at one point and then flowing out and converging at different points under general categories, like for Undergrad colleges, the lines converge around a circle for private, public or elite college, then the same for different types of graduate studies, and then types of careers like law firm, media, real estate, military, and the finally government like state legislator or public judge. The lines have this nice gentle curve to them when they change direction, and there’s not that much criss-crossing, which is obviously a result of Jessia’s meticulous design work. At the points that the lines converge like for public college, there’s a circle over the area and the size is proportional to the amount of lines are flowing through that point. That helps you get a better sense of how many lines are actually flowing through that point and compare against others more easily.

  • I think this was a really creative and beautiful way to give us a sense of the paths people took to congress - we get to see an overview, where the lines tend to gather the most, but you can also see individual lines and highlight specific congresspeople. Like it’s easy to see that a very popular path is to go to public college, law school, get a job in a law firm or business, and then serve as a state legislator. The lines are colored red and blue too so you can see patterns across the parties. So with this kind of visualization, you’re getting a lot of information about people’s paths through time, and the organic feel of the graphic kind of humanizing it a bit more which fits the topic really well. How can we create these?

  • Turns out others have tried and have encountered similar struggles getting it all arranged nicely. I turned to the members of the Data Visualization Society to see if anyone else has seen this kind of chart in the wild and Nicolas Krutchen and Gilmore Davidson sent me a ton of links (e.g. here and here).

  • There’s been a lot of work done researching a very similar chart called a Storyline visualization. It’s slightly different because the X-axis is strictly chronological. In the congress viz, the life events were generally grouped by when people typically reached certain milestones, like undergrad, graduate, career, congress, but obviously some members went to undergrad in the 80s and others not, so this chart isn’t strictly chronological. The storyline visualization seems to be used a lot in visualizing movies. Like every line is a character in the movie, and as the movie progresses, the lines group together when they’re in the same scene as each other. XKCD has a famous comic where he visualized Lord of the Rings in this way, which he called a Narrative Chart.

  • Inspired by this, Simon Elverly from the Australian Broadcasting Corporation created a similar chart to show how a political scandal unfolded. Each line was a person and they converged at different important events that they were involved in throughout the scandal.

  • If you want to try your hand at this, Simon posted his d3 code on github (plus his how-to post). It seems like the general consensus is that even if you use code to get the nodes mostly organized, you’ll still need to tweak the layout some for it to be legible. You can also do it all by hand. Or maybe make an alluvial diagram and then figure out a way to break it up into individual lines.

  • It seems like straightforward way to visualize events happening through time, but as with most things in data viz, as you start to dig in, you find it’s drenched in nuance…

  • My final takeaway is that the next time you need to visualize events are happening over time and how people were involved in those events, try a storyline or narrative chart. Having each person represented by one line really humanizes the data and makes it very engaging.

  • Finally, I asked Sahil and Jessia what’s their advice to designers just starting out, and Sahil said, “I think the magic of data visualization is being able to *contain* and *manage* complexity, not to get rid of it entirely. So, embrace complexity and novelty when you're sketching your ideas, and then show your work to a lot of people so you can figure out what kind of guidance the average reader will need to navigate your visualization.” And Jessia added “The story is told in the first 2 seconds”

  • Thank you Sahil and Jessia for sharing your inspiring project with us!

  • You can follow Sahil and Jessia on twitter, and keep following the New York Times for impressive graphics.

Episode 42: How to Use Audio to Enhance Your Data Storytelling - Featuring Duncan Clark

Welcome to episode 42 of Data Viz Today. Can we combine explanatory and exploratory data viz? That's just what Duncan Clark and his team over at Flourish are trying to accomplish by giving everyone the ability to create a "Talkie."

In this episode, find out what it is and how to create an effective one. Bonus: Duncan shares the one thing that would impress him in a data viz portfolio!

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

Transcript coming soon!

Links mentioned:

Episode 41: [Mini] How to Go on a Color Diet

Welcome to episode 41 of Data Viz Today. Are you terrified of color? Me too! :) Sometimes there are just too many choices. So I’m going on a color diet! What is a color diet? Well, for me, it means to be more conscious about how I use color in my visualizations to make sure that I’m using color to solve a problem. In this episode, we’ll talk about how a color diet can improve your work, plus a few tips on how to get the most out of the few colors that you do use.

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • Today is a mini episode where I talk about a data viz topic that I think is important. And today that topic is how to go on a color diet. What is a color diet? Well, for me, it means to be more conscious about how I use color in my visualizations to make sure that I’m using color to solve a problem and not just as visual entertainment. So in this episode, we’ll talk about how a color diet can improve your work, plus a few tips on how to get the most out of the few colors that you do use.

  • I don’t have any formal design training, like many people in the data viz field, so I never learned the ins and outs of color like a lot of people who come from like a graphic design background. So my color evolution went from just accepting software defaults, to changing defaults to other colors based on my whim, to where I’m at now where for personal projects I like to find colors that first make sense for my data, like is a diverging color palette appropriate or can I group these categories in a reasonable way so I don’t have 100 colors? And then I find other colors that are complementary, or pleasing to the eye as needed and color-blind safe. One of my favorite ways to find color palettes is to the Google Art & Culture Art Palette site which shows the palettes of tons of artworks, and then run it through Susie Lu and Elijah Meeks’ Viz Palette tool to make sure there aren’t any color conflicts.

  • But when it comes to picking color for work projects, I’m frozen into a panic. The choices feel super overwhelming the stakes seem so much higher. So I decided to go on a color diet and explore how to do more with less.

  • The first step in going on a color diet is to design your visualizations without color, using a monochrome palette, which means displaying images in black and white or in varying tones of only one color. Think of a color ramp from white to black and all the grays in between.

  • A big benefit of designing without color, is that you can really focus on the data first. Anand Satyan wrote a really great Medium article about the benefits to UX designers to design with no color. One of which is that you allow your eye to really see the layout and spacing of all your elements. Your eye isn’t getting drawn by color, so you notice how things are grouped, how readable is your text…

  • Another benefit is that the people you’re working with, clients, stakeholders, will start asking better questions when you show a monochrome design first. Anand says that you can have a conversation about what color works for which elements, rather than the conversation focusing on why you chose yellow.

  • So first designing without thinking about color will help you focus on your layout, spacing, alignment, hierarchy. And it’ll also help you and your client focus on HOW you’re using color rather than which colors you’re using.

  • That line I recently read in Scott Barinato’s new Good Charts Work Book, which is an amazing book that I’m working through with hands-on exercises. In the chapter about color, he wrote: “Think HOW, not WHICH.” And this itty bitty change in thinking was huge for me. It totally changed my perspective and anxiety around color. Instead of freaking out about WHICH colors to use, I first needed to think HOW. How will using color improve my reader’s understanding? How will this color in this spot make this viz more effective?

  • When your goal is to use color to solve a problem, the choices are a lot easier. Do you have a line chart of temperatures in 10 cities? The software default will give you 10 nice bright colors for each, but HOW is color going to improve your reader’s understanding? Maybe your point is to show how your city compares to other cities, so 9 will be gray and your city will be blue. Color has helped focus your reader on your story.

  • So how can you get the most out of using a monochrome palette, it can feel kind of restrictive at first, but I came across a presentation by the cartographer Daniel Huffman where he argues why you should design maps in monochrome. The presentation is only 10 minutes long, and definitely worth watching all the way through, but there were two tips in there about getting the most out of monochrome that I really liked.

  • One tip is say you have a map and you make the water white and the land gray. That would be my initial instinct if I were going to only use a white to black ramp. But now, the grays you have left for everything else are limited. But, you can get those grays back, if you make the water and land both white, and you just give a glow to the land so it looks like it’s popping up away from the water, or add concentric water lines to the coastline. So your reader can distinguish between the two, but you still have your whole color ramp to use for other things.

  • Another tip that Daniel had was to think about how you can use patterns, like diagonal lines or dots. This allows you to use one color of gray for a whole bunch of things.

  • If you think about it, some other benefits of designing in monochrome is that you don’t even have to worry about whether people are going to understand your viz if it’s printed out in black and white, or if your palette is color-blind safe!

  • My final takeaway is that designing your visualizations without color or in monochrome helps you in the design process by allowing you to focus on the layout and helps you focus on HOW color will help your reader. You can get the most out of using a monochrome palette by using techniques like glow or shadow, or using patterns. Once you max out your monochrome, think about how that one pop of red will make the HUGE impact you’re looking for.

  • I’m looking forward to going on a color diet and pushing my monochrome limits. If you have a pro-tip on designing without color, I’d love to hear! I’m on twitter at DataVizToday.

  • Join the Data Visualization Society HERE!

Episode 40: How to Add Small Multiples to Your Flow Charts - Featuring Chris DeMartini

Welcome to episode 40 of Data Viz Today. How can you add more information to your flow charts? Incorporate small multiples! In this episode, we learn about Chris DeMartini's data visualization that brings together small multiples and a flow chart (an NBA bracket) to add context to the flow. Find out how he created it, and how this technique can be applied elsewhere!

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • 00:15 - Today’s episode is all about small multiples but with a twist. If you haven’t heard the term small multiples before, it’s a term popularized by Edward Tufte, and it just means when you have a bunch of smaller charts of the same type using the same scales and axis that are bunched together showing different partitions of the dataset. It allows you to quickly compare information.

  • 00:46 - Recently I saw an interesting twist on small multiples, where Chris DeMartini incorporated small multiples into an NBA Playoffs bracket. He used the term Small Multiple Flows, which I’d never heard before, to describe when you add small multiples to a flow diagram. Even though I don’t have any interest in the NBA Playoffs, I began thinking about all the cool things you could do when you use that dead space of a flow chart or org chart or a timeline to add more detail.

  • 01:31 - Today’s featured project is called “NBA Playoffs 2018” by Chris DeMartini. Chris runs the Data Visualization team at Visa. He also works with DataBlick on consulting, non-profit and R&D projects. He has been a Tableau Zen Master since 2016.

  • 01:48 - Chris found himself a bit of a frustrated sports fan as he was following his favorite teams, like the Warriors, because when you look at sports brackets, you’re only getting the final result - who won and is advancing to the next round. But what if you want more info? Was it’s a blowout? Was it close?

  • 02:10 - He got inspired by how FiveThirtyEight does their brackets, where if you hover over a team, their bracket path to the championship changes thickness based on how likely they are to advance at each stage. Chris got the idea that he could use a similar idea where he’d encode data from the actual game into the bracket’s structure. So his goal was to have a visualization of the NBA playoffs that would give you a quick look at who is advancing but also give you an idea of the quality of the match-up.

  • 02:42 - He went through many iterations using pencil and paper to decide what information he’d encode and how he’d do it. Chris settled on a few things: First the line of the bracket was colored by the team that won the game, then the small multiple element encodes the (raw) cumulative score differential across for scoring play. So x axis is scoring play # and y axis is difference in total score as of that play. The chart is then encoded based on who has the lead on that play which carries through to lines, etc. So it’s really easy to see if there’s a lot of back and forth (data above the line, below the line) or if one team dominated. Then there were concentric circles behind each game to represent the number of wins for the team in that series. There’s a ton of info packed into this bracket! It’s a sports fan’s dream.

  • 03:42 - He said he got a lot of inspiration on how to layer all this information from vizzes around the community, but mostly from a viz by Nadieh Bremer about a Japanese Comic where she encoded a lot of data about the comic in this circular chart.

  • 04:01 - Once he figured out how he wanted to show all the info, he needed to implement it. He got the data from NBA.com and used Alteryx to get the data in a usable format. He said the data prep would’ve been the hardest part if it weren’t for Alteryx. Then he needed to execute all these encodings in Tableau. To do this, he used a technique that involves layering multiple tableau charts over each other. So in this case, he had one chart with the bracket and the colors of the lines of the brackets based on the winner, then another chart for the bars representing scoring plays, and another chart with the circles behind each game representing games won.

  • 04:45 - He has a detailed blog post about how to do this technique and another one specifically how he created this NBA viz. You can also download his Tableau workbook to reverse engineer his Tableau wizardry. You can definitely tell why he’s a Zen Master when you open it up.

  • 05:02 - So seeing Chris’ viz, really got me thinking about all the applications of this Small Multiples Flow chart. Like you could take something simple like the org chart of your team and use the lines and other elements to show extra information. Like if it’s a sales team, you can have a line chart associated with each person showing sales over time.

  • 05:25 - Or you could have a flow chart of different paths people take on your website, and add a bar chart for how many times people press the Buy button while they’re on that page. So you could see the typical path a customer could take through the website, and see that people press the Buy button quickly after landing on this one particular page, and maybe they take longer to press Buy on a different page.

  • 05:50 - It could also be a more simple flow chart, like events happening through time. Like it was recently President’s Day here in the US, and it got me thinking about Presidents and their approval rating. You could show the succession of presidents with their picture and name, and a line connecting each of them, so it’s a basic timeline of presidents, but in between each one is a small line chart showing the president’s approval rating throughout their presidency. Just this small tweak of making the timeline the main story of the graphic, and then adding data within that structure, is a really simple but interesting way to display your data.

My inspired viz - timeline of recent US Presidents and their approval ratings in between.

  • 06:40 - It might be cool to do something like this with networks too where nodes are connected with lines to show a relationship and there is another chart within those lines.

  • 07:00 - My final takeaway is that if your main story is the flow of the information, that doesn’t mean you have to leave out contextual information. You can integrate small multiples into the structure and give your audience the benefit of seeing the overall flow and extra details. So check out your flow charts and use all that space to your advantage!

  • 07:22 - Finally, I asked Chris what’s his advice to designers just starting out, and he said, “Just try it, don’t be shy, afraid or worried about what people think (which is easy to do these days, and I still do this constantly). Learn from others, be sure to site your sources and inspiration ALWAYS. Continue to evolve techniques and push viz forward in what you do.” Thank you Chris for sharing your inspiring project with us!

  • 07:47 - You can follow him on twitter @demartsc. And check out his great blog posts on the datablick blog.

Episode 39: [Mini] 3 Design Tweaks that Make a Big Difference

Welcome to episode 39 of Data Viz Today. I’ve been on a mission to improve my design abilities, and there are three design tweaks that I’ve found to be really effective in making my visualizations look more professional. In this episode, I share these three tips that pack a punch!

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • 00:15 - Today’s topic is 3 design tweaks that I’ve learned this past year that instantly improve the design of my visualizations. I’ll explain those three things, and I actually took an old chart that I had made and implemented these three things so you could see the difference. There are still a lot of things I’d change about that chart, but it’s interesting to see the transformation with just three tweaks. See below!

  • 01:10 - First, alignment. I try to make sure everything that I put on a page is aligned with something else, or there’s a really specific reason why it’s not. Usually I find left alignment looks best, especially with bigger chunks of text. In Adobe Illustrator, I’m always setting up my graphic with straight guidelines that I can use to snap all my elements to. You could mimic this in powerpoint or tableau by drawing your own guidelines along the margins or between groups of information. In Tableau dashboards, you can toggle on a grid by pressing the G key, which is super helpful. So be aware of what each element is aligning with, and also an alignment that’s easy to overlook - the vertical and horizontal spacing between your elements. Make sure there’s consistent space between your elements as well.

  • 02:10 - Second, text hierarchy. We talked about annotation hierarchy in episode 7 “How to Annotate Like a Boss” where you have a title, lead-in text right below it, then maybe subheaders and explanatory text within your chart to call attention to the points of interest. And all those text elements have an order that’s ideal for your audience to read them in. So how do you convey that order? Usually I go straight to size of the text, which definitely works well - bigger things are more important. And another option is weight. Many fonts of a light, regular, italic or bold option so you can layer those to create a hierarchy effect. Another way is color. One technique that I’ve been experimenting with is using a slightly lighter black, which can be easier to read that straight black, for the title, and then smaller text that’s grey for the subheader. Or for a white text that’s on a darker background, you can make text look less important by giving it a little transparency so it takes on a bit of the background color so it pops less than the white title. I’ve used this technique well with labeling. Like if I have a treemap and I’m labeling each segment with the category and the percentage, I write the category white and then the percentage in white with added transparency. It’s legible and cohesive because I’m not changing much, but it still gives a little hierarchy.

  • 03:50 - Third, keep annotations simple. After doing episode 26 “How to Develop Your Design Eye” I realized how crazy I was with my annotations. You can see in the shownotes for that episode, I had created a viz for rainfall in DC and then I came across a similar viz by Jane Pong for rainfall in Hong Kong a few years earlier so I had the unique chance to directly compare what I created with something a pro created with a very similar dataset. And one big thing that stood out is that Jane had these really elegant and understated annotations calling out interesting days with short, slightly curved black lines and text within the chart, and by comparison, my annotations looks almost comical because the lines were really long and flowy leading out to text outside the chart and colored red! Then I also had these big clunky arrows along the axes as if people didn’t know which direction to read. So now, I keep my annotation lines as short as possible, with only one curve (not bending in and out and around), and in a consistent thickness. Like the line doesn’t start small and get bigger. I’ve noticed that when I use arrows or lines that do that, it looks more clip-arty.

  • 05:30 - One resource that really helped me as a beginner is Canva’s Design School. They have a bunch of interactive tutorials and courses that do a good job of teaching some basics.

  • 05:50 - My final takeaway is that there are a few design tweaks that can get a lot of mileage out of. And for me, those have been making sure each element is aligned with something else, make sure your text has hierarchy with size, weight or color, and lastly, keep the arrows and annotation lines simple.

  • 06:30 - You can sign for my weekly newsletter that I send out every Sunday with top tips from the episode. I love mailing it out every week and getting your replies!

  • 06:35 - I also have a resources page with my favorite books, blogs and podcasts.

  • 06:45 - And I also have two online courses - one for creating your first custom map using Mapbox, and the other is a shortcut to learning how to create charts in Adobe Illustrator.

Here is an example of those three tips applied to an old viz. There’s still a lot of changes I’d make now to this viz, but doesn’t the new one look a little more professional with better alignment, clear visual hierarchy, and simple annotations?


My old visualization BEFORE tweaks

AFTER - making a few tweaks

AFTER - making a few tweaks


Allison Torbanmini, design
Episode 38: How to Use Writing to Improve Your Vizzing - Featuring Tiziana Alocci & Piero Zagami

Welcome to episode 38 of Data Viz Today. Can you write your way to data viz success? It might be hard to see how writing could improve your visualizations but in this episode, I'll lay out 3 compelling reasons WHY you need to start writing today. Plus, I'll share easy 3 steps to get you started.

This episode is inspired by the creative passion project Market Cafe Magazine that's created and independently published by Tiziana Alocci and Piero Zagami. Listen to what it takes to self-publish a data viz magazine!

Listen on Apple Podcasts, Google Play, Google PodcastsStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • 00:23 - Today’s episode is all about using writing as a way to improve your data viz skills. The project that inspired this episode is the data viz magazine called Market Café Magazine that’s independently designed, written and published by Tiziana Alocci and Piero Zagami.

  • 01:10 - In this episode, we’ll find out why Tiziana and Piero started a magazine about data viz, how they pull it all together, and how it’s changed their lives…Then I’ll jump into the reasons why YOU need to start writing about data viz too, plus 3 tips to get you started.

  • 01:35 - Tiziana and Piero are both accomplished freelance information designers in London.

  • 01:40 - In 2017, they were super active in their local data viz community - constantly going to events and conferences, and couldn’t get enough of consuming and creating visualizations. They started to feel this itch that they wanted to dig into the process of how designers were going about their craft, and share those stories in a unique and artistic way. The decided that they’d figure out how to curate stories from interviews with designers that they admire and make a magazine for the community to enjoy.

  • 02:20 - But a little wrinkle…they didn’t have any experience in journalism or publishing. So they obsessively started building a database of practitioners that they wanted to interview, topics that interested them and that led to research on templates for the content, and they began briefing contributors, and working with sub-editors. It started to come together and they kept experimenting and trying…

  • 02:55 - Being freelance made the process of putting the zine together a little easier since their schedules are flexible, but it still required a lot of sacrifice and long nights and a ton of visits to the post office.

  • 03:05 - They have 3 issues under their belt now so they’re slowly getting processes in place and more streamlined. It’s been taking them a few months to put together each issue because they take a very artisanal approach to creating the zine: they do tons of print tests, color studies, and image manipulation to apply this cool and unique look of their zine where each issue features two new colors.

  • 03:30 - But the 4th issue, due out very soon, has been 6 months in the making…Tiziana and Piero say that’s because while the mechanics are getting easier for them, they’ve found that they like pouring lots of time into researching right people to interview. Part of their secret sauce is interviewing all their contributors in person to make sure they can capture the human-side of every story. It’s admittedly time consuming and exhausting but non-negotiable in their opinion.

  • 04:11 - They use Adobe InDesign to create the layout of the zine and then work with a third-party printer to do a limited run of each issue. They have a unique point of view in the way that they put it all together so it’s an experience for me.

  • 04:40 - So crafting this magazine is obviously a labor of love, so why do it? Why write about data visualization? Tiziana and Piero have found that every time they interview someone, they not only learn about someone else’s experience who is probably socially and culturally different from where they come from, but they also get a fresh injection of knowledge and enthusiasm from this person. I’m sure you’ve experienced this before – talking to someone who’s really passionate about subject is very energizing.

  • 05:30 - Ok so writing about data viz has been fulfilling for Tiziana and Piero, but why would you want to write? Here are three reasons why writing can help you improve:

  1. It’s a creative outlet, you have complete control over what you write about and how you do it. You don’t need to create in the same way that you’re used to consuming it. And that exercise in creativity is great exercise for creativity in your visualizations.

  2. When you write and share, you’re inviting others to engage with you. You make new connections and broaden your network. Especially if you do interviews or collaborations. You make some talented friends that you can learn from. Related to that, when you write about your experiences, you’re helping other people. Maybe you don’t want to write about something because you feel like other people have already written about it, but the one thing that no one has - is your experience. The events that have happened in your life and your reaction to them. Those are unique to you that can help someone else. And I believe that no matter where you’re at, you’re one step in front of someone else and you always need to be looking back to see who you can lift up.

  3. You learn more about yourself and the topic by writing about it.

  • I noticed a tweet by Alberto Cairo not long ago, saying that he asks his Intro to Dataviz students to create personal blogs and write about their
    weekly readings. And I asked him why he does this and he said that he’s learned
    that the best way to memorize something and understand it well is to force
    yourself to write publicly about it. He asks them to not just summarize the content of the book but to connect it to their own experience. Read more in this post.

  • I’ve definitely experienced the benefits of this. By researching a topic, like the episode on box plots, and then weave it into a story and add useful tips, I really have to dig deep. It takes between 10 to 20 hours of work for each episode. And I’ve learned so much more than if I just read someone else’s post or a Wikipedia article.

  • BONUS why: career builder, you’re creating a body of work that’s showing how you think and your expertise. That’s pretty valuable.

  • 07:50 - Ok so those are some great whys, but how…I know that writing your own content is daunting for many reasons. But here are three quick steps that you can do now in just a few minutes that will make writing about data viz feel closer…

  1. Announce a schedule and keep it. Tweet it, tell your friends, or just text your mom. Just someone who will ask you about it so that you keep moving forward with it.

    • Being consistent is really where you can see growth and reap the benefits. Two posts a year isn’t going to move the needle.

    • I remember Seth Godin, the famous marketing guru who has been writing a blog post every day for years, he said the fact that he lives every day thinking that I have to write something worth reading tomorrow completely changes the way he navigates through life. He notices the little the things, he’s more in tune with things that pique his interest. I thought that was an interesting take – just the fact that you have to say something worth listening to on a consistent basis can make you up your game. Change the way you think. So make a schedule and keep it. Consistently write about your data viz experience.

  2. Think about who you’re writing for – narrow down your audience. It can really help you narrow down the topics you’re going to write about. Just start with an audience of one – yourself. Draw a circle that’s you – draw 2 or 3 lines coming out of your circle and write a few things that you like. Cooking, sports, podcasts, parenting, running, legos, videos…. Then draw a bigger circle around all of that. That’s your audience right now. You plus anyone else who likes the couple of things you like too.

    • I like short bits of data viz tips and podcasts. So here we are. I got a lot of questions about why I’d put a visual topic into an audio format, but that’s what I was interested in, and it turns out that other people are interested in it too! It’s not for everyone, but it’s helpful to some people, and that makes be really happy.

    • Tiziana and Piero like boutique artsy magazines, and stories about data viz designers. They gave me really great advice for anyone looking to start writing about data viz. They said, “keep it tight, specific to the topic you love, no matter how niche or weird (in fact, the stranger the better). Be honest, insightful, and establish a regular flow of content, so your audience can learn what to expect and when to find it.”

  3. Create a template – this is a content creation secret that I’ve found that the best bloggers use. Have a few general themes that you rotate through. It’ll help keep you focused and feels less intimidating when you sit down to write.

    • Here’s an example: If you’re blogging once a week, first one is a new technique you learned, second week is the process behind a new viz, third one is your opinion on something you read or a piece of news, and fourth week is the best viz you came across that month and what you liked about it.

    • And within that kind of template, keep in mind that the best posts do three things: Inspire, educate, entertain. If you can do all three within a post, amazing. But I’ve found it easiest to focus on one to be the star and have the other two be co-stars. If you couldn’t tell, the star of this episode is inspire.

  • 11:55 - So you got your schedule, you narrowed your topics a bit by your interests, and then write your template or general themes that you’ll use within your schedule. Then you sit down to write your post, think about what’s the star of this post – am I tying to inspire, educate, or entertain?

  • 12:20 - My final takeaway is that if you consistently write about your experience in the visualization field, you can start reaping the rewards of having a creative outlet, making new connections and helping others, really learning and going deep on the details, and building your own body of work that can help your career.

  • 12:55 - You can keep up with everything Market Cafe Magazine on twitter @MarketCafeMag and snag an issue here: https://marketcafemag.bigcartel.com

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