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Friday is tool day! Datawrapper is one of my all time favorite data design tools, watch the video to learn why.

Transcript

Hello. So this week, I thought we try something new on Fridays. I was thinking, maybe we talk about tools like different pieces of software. That could be helpful to you. If you were trying to do any type of information, design data design work. So that’s what we’ll talk about today. All right. Let’s start with the problem. If you’re creating reports. You need to create more than just the one pager, the three pager that 30 pager. In the modern setting. Because we need to reach more audiences. It’s harder to reach those audiences. So we need more things out there in order to even hope. To reach a broader audience. So that means we have to create a lot of reports and that means a lot of charts and that sort of thing.

So it’s one thing to say it would be great if we had tons of money and we could invest more time in reporting. But that doesn’t really happen. Really? It’s the same amount of time you just are expected to create more reports. So you need to change your process, need to have tools that let you create things faster.

Some of those tools are tools that are built for data, journalists or journalists in general. If you think about it newspaper creates tons of charts and they have to create charts on a regular basis. And they have, especially if they’re reporting daily or even weekly that’s a lot of charts they have to create.

And they have to be publishable quality and ready to go. So there are a few tools out there that help you with this. And one of my favorites is a tool called data wrapper. You’ll find it at data, rapper dot D E. It’s one of the eights, one of these new types of tools that really starts. Close to a professional looking professional quality chart.

You don’t have to do much for it. Once he created a really easy to share. It’s not like you’re working in Excel and you have to like, almost break down everything to create something that’s ready to be published. It’s ready to be published right off the bat. It’s also not complicated, like Tableau or power BI or anything. You’re not diving into huge datasets and trying to reformulate everything.

It’s really a chart builder or a map maker. A modern kind of data, visualization chart and map and table tool. There are a few things that you should know about it. One, the price. It is either free or lots of money. This is one of the things about these kind of journalism dataviz tools.

They have fantastic free plans link. You can do so much with the free plan. They’re forever free. Not like trial version kind of free plans. But if you wanted to actually pay for it you need like, 600 a month and it’s for a team that kind of thing. So there was not really a price point for somebody who’s just an individual designer, that sort of thing.

Luckily, you can do tons with the free plan, so you don’t even have to pay for the pro plan. One day, maybe they’ll have an individual pro plan. And if anyone from data wrapper is watching maybe 80 bucks a month, a hundred bucks a month for an individual plan might not be a bad idea. But until that happens.

Free is great. Let’s keep it free. All right. Better faster. So that’s what we’re trying to do. We’re trying to not be overwhelmed. Data wrapper. Sets it up. It’s 1, 2, 3, 4 steps to a chart and they walk you through step-by-step. So you start with the data, then you work into the design and then some other factors. And then finally you get to the publishing part of things.

And they really walk you through the process, make it really easy. All your data is private by default. This isn’t like Tableau, public. It’s not going up to a public server immediately. It is private. You don’t even have to log in to data wrapper in order to create charts.

You can just go to data, wrapper dot D E, open it up, run through the process.

Data wrapper is GDPR friendly. They don’t track. Make money selling other people’s data. So that’s an important aspect here too. A lot of companies do. Not this one. It really is a high quality company, I think. So hopefully it stays that way, but right now I am a big fan of data wrapper as a company.

And then finally accessibility. This is one of those afterthought kind of things. It’s one of my biggest gripes with tools like Canva is their lack of accessibility tools. With data wrapper there, just like you can test different types of colorblindness. On the actual charts, it’ll show you what it looks like for different people. So you can test your, colors and that sort of thing. It gives you a really easy way to do alt text.

Which is also really useful. And then you can embed these charts in other places. Just straight from data wrapper. You, once you log in, you’ll have a library of your charts. And that’s a reason to log in, or you can just save them as PNGs and put them out elsewhere like that. So that’s my tool of the day.

Today’s data wrapper. So again, data wrapper. Dot D E it’s a German company. And yeah. Check it out, play with it. It’s super fun. Have a great weekend. And I’ll talk to you soon. All right. Bye.

In today’s vlog I walk through 5 of my favorite quantitative data dashboard design tips.

Transcript

Okay. So last week I fielded a question about data dashboards. And in that particular video, I talked about why they failed and why you might want to consider using a website instead of a regular kind of dashboard. Uh, quantitative dashboard. But I also know that there are plenty of you that have tons of quantitative data and just want to create. The regular kind of dashboard that you see all over the place.

So let’s get into that today. You know, I, I think that issue. The thing that we should talk about first. Are the reasons why we have this data dashboard in the first place. So this is a person. Okay. I don’t even know what exists. And that’s true. A lot of the time.

There are a lot of data sources within organizations that. Are not necessarily accessible to the decision-makers stakeholders who could really get a lot of value out of that data. So that’s the reason why a lot of dashboards are created or at least the theory behind creating dashboards.

And I’ve talked about this a little last week, but.

I see dashboards as being an interface between the data and a user, some user. So. It can be hard to. Have a person just go, okay, well, I want to access some data. I’ll just go into SQL and pull some data and then I’ll analyze it and pull it up over here. That just doesn’t happen. I mean, some people it does, but most people, it does not happen. You have to reformat data most of the time to make it useful.

It’s a resource. You have to process it. In some way. And when you process it, our goal really is to reduce the amount of overwhelm. Because it can really quickly, we can get overwhelmed by the amount of data. And depending on who you are. I mean, there are some organizations like places like a retail establishment.

Are analyzing tons and tons and tons of data. And that data is you cannot access it. Most research and evaluation data is a little different though, because it’s accessible enough. You could probably pull it up in Excel and just put together some pivot tables and do some analysis.

Even so it’s enough data that having some kind of interface makes sense. So what are my tips? Well, let’s go through five. I think. Yeah, about five. Alright. Tip number one. It does not have to look like a car dashboard. Like it doesn’t have to have the little gauges or look like it’s speed limit thing.

Everything doesn’t even have to fit on one page. You can have it. So it’s up and down. Scrolling, scrolling, scrolling, actually that’s a much better idea most of the time than having anybody click on anything. ’cause. I don’t know if you know this about people, but they’re pretty lazy. They don’t like clicking on things.

So something has to be really valuable for somebody to click. That’s why so many social media sites. Now you just have the endless scroll, scroll, scroll, scroll, scroll, scroll. Well, you can develop dashboards in the same way. All right. Tip number two. It really comes down to familiarity and frequency.

Um, in terms of how you would design your dashboard. Alright. If you are really familiar with the data. Where if the, the people, the user that you’re trying to reach is really familiar with the data. It doesn’t really matter how it’s formatted. I mean, you just give them tables, you give them numbers. They’re going to understand it.

So they’re very familiar. And you have a lot of data. You create a dashboard. If they’re very familiar and you have a little bit of data, you create some kind of report. It doesn’t really matter what it looks like. They’re going to get it. If they’re not so familiar or they need to be introduced to the data.

Then you need an engaging report if it’s less frequent and if it’s more frequent, then you need some kind of annotated engaging dashboard. The idea is that we have to not Jess. Deliver the data and the information, but we also have to deliver the context behind that. So we have to walk our user through it.

All right. Tip number three. Um, and this is particularly useful for researchers and evaluators.

If something’s useful. Um, and insightful. That’s what you want to put into a dashboard. You want something useful?

I know a lot of researchers and evaluators who will look at a dataset and they will systematically start analyzing it and pulling it apart. And then pull it into pieces in a dashboard. Like you have to share all that stuff. But a good dashboard. Isn’t just a set of comprehensive documentation. It’s not just replacing a big table with a bunch of charts.

You know, it is something that is supposed to be useful. So that means picking and choosing, deciding what’s valuable. What’s not valuable. And you can use some different UX. A user experience design approach is user interface. Design approach is card sorts. Stuff. I’ll talk about in future episodes.

All right. The interactive design mantra. Um, I learned this pretty early on by Shneiderman. Um, I think that’s the name. I hope I didn’t just mess it up, but if I did, I’ll go back and change it. All right. So wait. There are three things. Overview first. Zoom and filter details on demand. The idea is.

When we’re developing dashboards that are interactive. There’s a different level, a different element. And that’s that you can explore, you can dive into it. So it means approaching the data in a little bit different way. And yet, sometimes that means starting from a. Bigger picture kind of point of view.

And then allowing people to zoom in and filter on the things that they really want to know. And then when they want more details, they click and they can get details. Right? So you have an overview then you can filter. This is like, if you see a dashboard in shifts, like a full country, And then you have, like, let’s say it’s the us.

And you have a dropdown filter and all the states are in the filter and you can click from the U S as a whole to individual states. So that’s your filtering. And it lets you zoom into different states. Maybe you can even zoom on the screen on a map. And then when you want more information about a particular area, you click and it gives you details. So that’s kind of how you design it.

Um, it’s a little bit different than designing a regular report. But. That’s pretty much it. All right. And the other thing is stay consistent. It’s great. If you know how to create lots of different chart types. But you don’t have to create lots of different chart types. Actually, it probably takes away. Anytime you change your chart, you kind of put that in somebody’s head that they have to like understand a new type of chart.

It’s better. If all the data is similar or kind of on similar dreams to, you know, just use bar charts, line graphs, scatter plots, these are all through things that are clickable filterable. Zoomable so they’re really nice charts to use in these kinds of situations. I’d avoid pie charts most of the time, unless you only have a couple of numbers.

I’d avoid, um, anything too complicated. I would. Try to avoid using, uh, multiple axes and anything too, like crazy. It’s better to do something simple. And repeated over and over and over again, then to jam everything into one chart. Which is usually what people try to do. When they try to turn it into a car dashboard.

So full circle, don’t do a car dashboard. Let it flow. Um, Yeah. If you have any questions, any requests for future? Episodes of this vlog. Let me know. I did get a request about doing something on qualitative dashboards. And we’ll talk about that next time, or I don’t know, in a couple of vlogs, we’ll see how things go.

But if you have any requests, please let me know. Again, just visit my site, down below, leave a comment here on YouTube. For how send me an email, do something like that. Either way. I hope you have a great day and we’ll talk soon. Alright. Bye.

You know the audience is important, but how do you actually design a report for one? My suggestion, design your report for 3 audiences.

Want to buy my book? You can get it here.

Transcript

Okay. So today I’m wanting to talk a little bit about your reporting audiences. Now, this is something. If you’ve actually read my book, the reporting revolution available on Amazon. In chapter two. I talk all about finding your audience. And you’ll see this little chart here. And so if you’ve read it, that’s actually what I’m going to talk about today.

You can skip it. Just share it with other people, tell people to buy the book, for other people, that kind of thing. Anyway. One thing to, to know. Or one thing to ask you is, do you know what the 1, 3 25 a report. Thing is.

Basically it’s when you create a report you should have 25 page report, a three page executive summary and a one pager.

Now, at least this was written pre-web early days of the web. I don’t know if it really holds up it’s a good rule of thumb. If you’re just trying to create a set of reports and just want to go the old school way. But I really think it hints at. Three different audiences.

And our need to serve multiple audiences at once. Serving a whole bunch of audiences. As many of us try to do with our reports. Is one way to get overwhelmed really quickly because you start listing off audiences. And if you try to create reports for all of those audiences, you’re going to become overwhelmed.

And you’re not going to create anything good. That tends to be what happens? You burn yourself out. So we want to avoid burning you out. But basically we can think about our audiences as just being three different entities. And if you can at least use this as a starting point. Create for these three audience members.

And you’ll be a bit better off. You can add more if it’s important later specific types of people that you want to try to create for, but let’s start with this. The first audience, the 25 pager audience is your high interest audience. They’re the ones who want everything. They’re really invested in your work. So they want to be kept up to date. Maybe your work is really relevant to what it is that they do on a day-to-day basis. Maybe you just write really good reports.

This is your audience. That is the high interest. This is the one that they’ll read, whatever you write. So your comprehensive stuff, your data dashboards that you put out. Unfortunately, most of our audiences are not that audience. Most of our audiences are either medium or low interest or casual. Medium interest is an important one, because this is usually our boss, the executives that politicians were trying to reach.

There are people that might have an interest in our work and what we’re trying to do, but usually they’re pretty busy with other stuff or they’re. They have their own overwhelming stuff going on, busy calendars, all that stuff. So reaching them is more about. Figuring out what it is about them, that they would find interesting.

To see in your report. So this is how you design presentations, executive summaries. Even some kind of visual reports. Slide docs and shorter reports that you share online things that these are things that are designed for your medium interest audience. And our last audience is probably the biggest number of people.

Is our low interest or casual audience. This is our like social media following people who are somewhat connected to your work. They don’t, they’re only gonna read what you have to write, what you share with them. If it is particularly relevant. To what it is they’re doing at any given moment.

So that’s the whole idea around one pagers, infographics, micro graphics, short kind of videos. These types of things are designed for low interest audiences. It’s about making a connection. And All of this is fluid. Low interest audience member can become medium interest or high interest.

And they can go back and forth. And depending on what you’re writing about, depending what your report is about, but these are three general audiences that you can think about. And. If you try to put names to these people, sometimes it helps to. But I hope that helps try that. Next time you go into reporting, try to think about three audience members, your high interest, low interest, and medium interest.

And see how that changes the way you report. Try to create a report. Designed for each one of those levels. And I think you’ll come up with something interesting. So good luck. Talk soon. Bye.

In this video I’ll walk you through the 4 things you need to consider when developing your own data to action strategy.

Transcript

?All right. So today let’s talk about the few different things that you need to think about. If you’re going to develop a data to action strategy. We have data. And we have people who want data. And the truth is. Lo longer. Time goes, the more data that we have and the more overwhelmed these people get.

The further apart they go. It’s hard for this person to access the data, at least where it lives. So we need to connect the two. And there are two ways that we generally connect it. The first way is through data people. This is like your researchers and evaluators. These are the people that this person says, Hey, I need data. And these people respond and they say I can get that for you.

And they go over here. They do some exploratory data analysis. Maybe they just understand certain datasets what’s being stored so that they can communicate with this person. Now just having people. Go get your data for you. It’s not really a scalable solution. And chances are we want to have more people access our data.

Therefore more decisions can be made using that data. So more action can be taken. What we do too, is we have a reporting strategy. And our reporting strategy has presentations dashboards, these kinds of things. They form a connection between the people that need the data and the data itself.

So those are the connection pieces. There are a couple of things that these people need to know in order to create these kinds of things. One of the things that we need to know is just what data exists. This is general data governance because it’s not just what data exists, but what do we have access to? What’s easy to access. How do we go about accessing that data?

How do we get it put into our dashboard? What’s public. What’s not public. Does this person have the authority to see it? All of those questions need to be answered. If you’re coming up with a strategy about making use of data. And we also need to think a lot about user needs. So this is the user experience component.

And I’d say these are the four things that we really need to think about. We need to. Come up with a reporting strategy. We need to build the capacity of. People in our organization to be able to go get the data, analyze the data and bring it to a person in a way in which makes sense. These are also the people that are creating the reports. So this is your data capacity building or data culture building.

Growing. We have our reporting strategy here. So the more we can make it a systematic kind of reporting strategy, the better off we would be. We need to think about user experience design. What are the user needs? What do people actually need to understand the data? And not just okay, they need such and such data, but what is it exactly about the data that they could use that would help them make their decisions easier?

Bring them to action faster. And then all those little data governance pieces we talked about in a minute ago. And if you have all those four things, you can really come up with a. Useful data to action strategy. So that’s it. Think about your data people. Think about your reporting strategy.

Think about your user experience? And think about. Your general data governance. What data you have available? What you might have available if you ask someone nicely. That kind of thing. And that’s it. So good luck. And I’ll talk soon. Alright, bye.

In this vlog I talk about what I think is the biggest reason why many data dashboards fail.

Transcript

?Thank you. So last week I asked the people who follow my newsletter. If they have any topic requests. And I had this nice little email I got from Dr. Maria-Theresa Okafor, she says happy Wednesday and thanks for the opportunity to weigh in on your vlog topics. I would love to see a vlog on dashboard creation and dashboard tips.

Now I thought that was a great idea. Although I think it might take me more than just one vlog, but that’s okay. I think today, really what I want to go into is the first thing. Why do so many data dashboards fail? Like, why are they bad? I have a cartoon on this, actually, one of my favorite cartoons.

And in it. It looks like this, isn’t the actual cartoon is not much better drawn, but it, does have a full cartoon. The one person, there are two people there sitting in a car. Here’s the dashboard over here. And the one person says, why is this spedometer stuck on 35?

And the other one says the car only collects speed data once a year. And. That’s the issue. Is that when people create data dashboards, a lot of the time they create imagination dashboards. Things that are purely fictional, they have all these great ideas for everything that’s going to be in the dashboard.

And then they get to the dashboard and they’re disappointed in what they see. It’s not necessarily because they might blame the dashboard tool or the design. They might blame themselves for designing a bad dashboard. But it actually has nothing to do with the dashboard or the tool. It has to do with this.

See. To understand a dashboard. We have to understand what it is that a dashboard is supposed to do. And a good dashboard is a connection point between lots of data and a person. At least from a research and evaluation sense. There is a little bit of, okay. What knowledge do you, what information do you have to know on an ongoing basis to make decisions? So if you think about a car, knowing your speed at a given point in time tells you if you need to slow down or speed up at the speed changes, you can.

You can act accordingly. You don’t just have to guess at your speed. But a lot of times when we’re creating dashboards for research and evaluation, It starts with this idea that there’s a lot of data out there. That we have access to. And we have people in our organizations. We have stakeholders, audience members managers, all sorts of people who need access to this data.

But we can’t just give it to them it in the raw form. We have to create something in between. An interface for this data. And that’s what a dashboard really is. It’s essentially a user interface for datasets and data tables. And if you think about that it makes sense. Why. This dashboard, of course doesn’t work.

Because this dashboard. Doesn’t have lots of data. And the challenge is this is what we see when we see most dashboards we just see the person and the dashboard. We often don’t see the data behind the dashboard. So the data doesn’t exist. We see the same thing. Whether we have tons of data or we have no data.

And ultimately when we have no data, it doesn’t make sense to make a dashboard at all. And that happened so often. Research and evaluation where a team will make a dashboard where a dashboard just does not make sense. I would say that the vast majority of the time a website is going to be better than a data dashboard.

And this goes for anything that has a lot of qualitative information, anything. That is infrequently updated. So let’s say quarterly yearly, these kinds of things don’t need data dashboards. They just need reports that are all updated often. Even some basic interactive data, if the data that you’re sharing is variable, that you’re offering different metrics at different times.

That’s also a place where you’re probably better off with a website and then the data dashboard. And then multiple audiences. That’s another place where people create these convoluted dashboards because they’re trying to create for too many audiences. So hope that helps. That’s the idea of why do many dashboards fail?

Next time around. I think one thing we’re going to talk about. Next is we’ll talk about building a good user interface for a data user interface, so good dashboard. And we can talk about tips like that in the future. We can also talk about. Building reporting websites or report blogs. Because I think they’re under utilized and we could do a lot more of them.

So thanks for watching. Let me know if you have any topic requests you can let me know in the comments or you can head to freshspectrum.com. Join my newsletter, where I send it out each week, ask people for requests. You can always send me one there. Otherwise. Check out my website and.

Subscribe to this channel and we’ll talk soon. All right. See you later. Bye.