Accessibility, Data Visualization, Microsoft Technologies, Power BI

Stop Letting Accessibility Be Optional In Your Power BI Reports

We don’t talk about inclusive design nearly enough in the Power BI community. I was trying to recall the last time I saw a demo report (from Microsoft or the community) that looked like consideration was made for basic accessibility, and… it’s a pretty rare occurrence.

A woman, man, and another man in a wheelchair next to the Power BI logo.

Part of the reason for this might be that accessibility was added into Power BI after the fact, with keyboard accessible visual interactions being added in 2019 as one of the last big accessibility improvements. But I think the more likely reasons are that inclusive design requires empathy and understanding of how to build reports for people who work differently than ourselves, and Power BI accessibility features take time and effort to implement. While we can never make our reports 100% accessible for everyone, that doesn’t mean we should just not try for anyone.

Population statistics tell us that many of our colleagues have or will have a disability at some point, and many of them will be invisible. So even if you don’t see a report consumer with an obvious disability today, that doesn’t mean an existing user won’t acquire a disability or a new user with a disability won’t come along as people change roles in an organization. In addition to the permanent disabilities we normally think of, there are also temporary and situational disabilities that we should try to accommodate.

In order to start designing more inclusively, we need to increase conversation around accessibility requirements and standards for our reports. I fully understand that it can feel tedious or confusing as you get started. I hope that as Power BI matures, the accessibility features will mature as well to make it even easier to create a more accessible report by default. For now, the only way to make accessible Power BI report design easier for report creators is for us to start forming accessible design habits and to offer feedback to the Power BI team along the way.

My Accessible Report Design Proposal

This is what I would like to see from report creators in the community as well as within Microsoft. I’ll define what I mean by accessible report design in the next section.

  • Before publishing a report, implement accessible design techniques as thoroughly as possible.
  • For demonstrations of report design/UI techniques where you are providing a finished product at the end, implement accessible design techniques as thoroughly as possible.
  • For demonstrations of things that are not inherently visual, implement bare minimum accessibility or add a disclaimer to the report.
    Example: “Here’s a cool DAX technique that I just threw into a quick table or bar chart to show you the results. It hasn’t been cleaned up and made accessible (alt text, color contrast, etc.), but I would do that before publishing.”
  • For demonstrations of report design/UI techniques where you show only part of the process, implement bare minimum accessibility or add a disclaimer to the report. 
    Example: “This is the part of the report creation process about creating bookmarks, and before I publish to an audience, I want to make sure I’m following good design practices including accessibility.”

Power BI Report Accessibility

I have a full list of things to check here. That is the checklist that I use to ensure my report designs are generally accessible, when I have no specific compliance requirements or knowledge or any specific disabilities that need to be accommodated. In my opinion, this is what we should be doing in all of our reports because we want everyone in our intended audience to be able use our reports. You’ll find a very similar checklist on Microsoft Docs.

If you need to start smaller, you can go with my bare minimum accessibility and work your way up to the full list.

Bare Minimum Accessibility

This is the short list of the most impactful (according to me) accessibility changes you can make in your report. Use this because you have to start somewhere, but realize there is more we should be doing.

  1. Ensure text and visual components have sufficient color contrast
  2. Use descriptive, purposeful chart titles
  3. Avoid using color as the only means of conveying information
  4. Set tab order on all visuals in each page
  5. Remove unnecessary jargon and acronyms from all charts

Give It a Try

I just learned that the Power BI Community Featured Data Stories Gallery theme for September is Accessibility. So here’s your chance to win a free t-shirt and internet bragging rights by showing off your accessible design skills. You need to submit your report to the Data Stories Gallery by September 30th in order for your submission to be considered. But a well designed, accessible Power BI report added to the gallery is appreciated any time of year!

Accessibility, Data Visualization, Microsoft Technologies, Power BI

Fun with Power BI and Color Math

I recently published my color contrast report in the Power BI Data Stories Gallery. It allows you to enter two hex color values and then see the color contrast ratio and get advice on how the two colors should be used together in an accessible manner.

Screenshot of the Color Contrast calculator Power BI report. The report headline reads "How shoudl I use these colors together in my Power BI report?". There are 2 slicers that allow you to select colors by hex value. A contrast ratio is shown along with advice generated on how to use the colors.
Color contrast calculations in a Power BI report

I could go on for paragraphs about making sure your report designs are accessible and useful for your intended audience. But this post focuses on how I made this report.

The Calculations

Color contrast (as calculated in the WCAG 2.1 success criteria) is dependent on luminance. Luminance is the relative brightness of any point in a color space, normalized to 0 for darkest black and 1 for lightest white. In order to calculate color contrast you must first get the luminance of each color.

As an example, I have colors #F3F2F1 and #007E97. In this hex notation, often explained as #RRGGBB, the first two digits represent red, the second two digits are green, and the last two digits are blue. Each two digits is a value that represents the decimal numbers 0 to 255 in hexadecimal notation. The same red, green, and blue values can be represented in decimal notation as integers, and this is what is used to calculate luminance. #F3F2F1 is RGB(243, 242, 241), and #007E97 is RGB(0,126,151).

On a side note, there are places in Power BI where we can change the transparency of the color which is referred to as RGBA (where A represents opacity/transparency). But whenever you copy a hex color value out of the color palette in Power BI, you will just see the 6 digits without the A because the A is stored separately in the UI. When you set colors using DAX formulas, you can specify the A value.

The sRGB color space is non-linear. It compensates for humans’ non-linear perception of light and color. If images are not gamma-encoded, they assign too many bits or too much bandwidth to highlights that humans can’t distinguish, and too few bits to shadows to which humans are sensitive and would require more bits to maintain the same visual quality. To calculate luminance we have to linearize the color values.

For each color component (R,G,and B), we first divide our integer value by 255 to get a decimal value between 0 and 1. Then we apply the linearization formula:

  • if R sRGB <= 0.04045 then R = R sRGB /12.92 else R = ((R sRGB +0.055)/1.055) ^ 2.4
  • if G sRGB <= 0.04045 then G = G sRGB /12.92 else G = ((G sRGB +0.055)/1.055) ^ 2.4
  • if B sRGB <= 0.04045 then B = B sRGB /12.92 else B = ((B sRGB +0.055)/1.055) ^ 2.4

Note: You will find sources online that that incorrectly use the number 0.03928 in the linearization formula instead of .04045. My understanding is that this is incorrect for sRGB.

Then we plug those values in to calculate luminance:

L = 0.2126 * R + 0.7152 * G + 0.0722 * B

The luminance of #F3F2F1 is .8891. The luminance of #007E97 is .1716.

The final calculation is color contrast:

(L1 + 0.05) / (L2 + 0.05), where

  • L1 is the relative luminance of the lighter of the foreground or background colors, and
  • L2 is the relative luminance of the darker of the foreground or background colors.

The color contrast between #F3F2F1 and #007E97 is 4.24, and we usually write this as 4.24:1. You can check my math here.

The Dataset

The source data for the report is generated entirely in Power Query. It starts with a simple list of the integers 0 through 255. I placed this in a query called Values.

let
    Source = List.Numbers(0,256),
    #"Converted to Table" = Table.FromList(Source, Splitter.SplitByNothing(), null, null, ExtraValues.Error),
    #"Changed Type" = Table.TransformColumnTypes(#"Converted to Table",{{"Column1", Int64.Type}})
in
    #"Changed Type"

My linearization function is called ColorConvert.

(colornum as number) =>
let 
    Source = if colornum < .04045 then colornum/12.92 else  Number.Power(((colornum+0.055)/1.055),2.4)
in
    Source

My main query is called color 1. This is where all the calculations through luminance are done.

let
    //Get values 0 - 255
    Source = Values,
    //Call that column R for Red
    #"R Dec" = Table.RenameColumns(Source,{{"Column1", "R Dec"}}),
    //Crossjoin to Values to get Green values 0 - 255
    #"G Dec" = Table.AddColumn(#"R Dec", "Custom", each Values),
    #"Expanded G Dec" = Table.ExpandTableColumn(#"G Dec", "Custom", {"Column1"}, {"G Dec"}),
    //Crossjoin to Values to get Blue values 0 - 255
    #"B Dec" = Table.AddColumn(#"Expanded G Dec", "B", each Values),
    #"Expanded B Dec" = Table.ExpandTableColumn(#"B Dec", "B", {"Column1"}, {"B Dec"}),
    //Get hexidecimal values for R,G,B
    #"R Hex" = Table.AddColumn(#"Expanded B Dec", "R Hex", each Text.End("00" & Number.ToText([R Dec], "x"),2)),
    #"G Hex" = Table.AddColumn(#"R Hex", "G Hex", each Text.End("00" & Number.ToText([G Dec], "x"),2)),
    #"B Hex" = Table.AddColumn(#"G Hex", "B Hex", each Text.End("00" & Number.ToText([B Dec], "x"),2)),
    //Concatenate to get full 6-digit Hex color value
    #"Changed Hex Type" = Table.TransformColumnTypes(#"B Hex",{{"R Hex", type text}, {"G Hex", type text}, {"B Hex", type text}}),
    #"Full Hex" = Table.AddColumn(#"Changed Hex Type", "Hex", each [R Hex] & [G Hex] & [B Hex]),
    //Convert integers to decimals and linearize
    #"R Lin" = Table.AddColumn(#"Full Hex", "R Lin", each ColorConvert(([R Dec]/255))),
    #"G Lin" = Table.AddColumn(#"R Lin", "G Lin", each ColorConvert(([G Dec]/255))),
    #"B Lin" = Table.AddColumn(#"G Lin", "B Lin", each ColorConvert(([B Dec]/255))),
    //Calculate luminance with the linearized values
    #"Luminance" = Table.AddColumn(#"B Lin", "Luminance", each 0.2126 * [R Lin] + 0.7152 * [G Lin] + 0.0722 * [B Lin]),
    #"Changed Luminance Type" = Table.TransformColumnTypes(#"Luminance",{{"Luminance", type number}}),
    //Create a column for hexidecimal value with the hash/pound at the beginning
    #"Hex Dup" = Table.DuplicateColumn(#"Changed Luminance Type", "Hex", "Hex With Hash"),
    #"Hex with Hash" = Table.TransformColumns(#"Hex Dup", {{"Hex With Hash", each "#" & _, type text}}),
    //Remove Hex and linearized RGB columns to keep model under 1 GB limit for Pro license
    #"Removed Columns" = Table.RemoveColumns(#"Hex with Hash",{"R Hex", "G Hex", "B Hex", "R Lin", "G Lin", "B Lin", "Hex"}),
    //Rename Hex with Hash to Hex
    #"Renamed Columns" = Table.RenameColumns(#"Removed Columns",{{"Hex With Hash", "Hex"}})
in
    #"Renamed Columns"

In order to allow users to choose two colors, I made a reference query to Color 1 called Color 2.

let
    Source = #"Color 1"
in
    Source

If you are interested in these Power Query scripts, you can get them from this Gist.

DAX Calculations

The color contrast calculation is a DAX measure because it is dynamically calculated based upon the colors selected in the report.

Color Contrast = 
If( Max('Color 1'[Luminance]) > MAX('Color 2'[Luminance]),
    Divide((Max('Color 1'[Luminance]) + 0.05) , (Max('Color 2'[Luminance]) + 0.05)),
    Divide((Max('Color 2'[Luminance]) + 0.05) , (Max('Color 1'[Luminance]) + 0.05))
)

The advice given based upon the color contrast ratio is also a DAX measure.

Advice =
IF (
    [Color Contrast] < 3,
    "Not enough contrast for text or non-text content, use only for decorative items",
    IF (
        [Color Contrast] < 4.5,
        "Appropriate for large text at least 18pt, bold text at least 14 pt, or non-text content",
        IF (
            'Color 1'[Color Contrast] >= 4.5,
            "Appropriate for any size text and any non-text content"
        )
    )
)

The example charts showing the two colors as foreground and background are SVG measures.

Chart 1 =
VAR Bkgrnd =
    MAX ( 'Color 1'[Hex] )
VAR Frgrnd =
    MAX ( 'Color 2'[Hex] )
VAR chart = "data:image/svg+xml;utf8,<svg xmlns='http://www.w3.org/2000/svg' width='100' height='100' viewBox='0 0 24 24' style='background-color:" & Bkgrnd & "'><path fill= '" & Frgrnd & "' d='M7 19h-6v-11h6v11zm8-18h-6v18h6v-18zm8 11h-6v7h6v-7zm1 9h-24v2h24v-2z'/></svg>"
RETURN
    chart
Chart 2 =
VAR Bkgrnd =
    MAX ( 'Color 2'[Hex] )
VAR Frgrnd =
    MAX ( 'Color 1'[Hex] )
VAR chart = "data:image/svg+xml;utf8,<svg xmlns='http://www.w3.org/2000/svg' width='100' height='100' viewBox='0 0 24 24' style='background-color:" & Bkgrnd & "'><path fill= '" & Frgrnd & "' d='M7 19h-6v-11h6v11zm8-18h-6v18h6v-18zm8 11h-6v7h6v-7zm1 9h-24v2h24v-2z'/></svg>"
RETURN
    chart

The check or x mark to indicate whether the colors can be used together in a graph or in text is created using Unicode characters.

UseInGraph =
IF ( [Color Contrast] < 3, "✗", "✔" )
UseInText =
IF ( [Color Contrast] < 4.5, "✗", "✔" )

The RGB value shown for each color in the report is a DAX measure because storing it in the model made the model size larger than 1 GB, which would have prohibited me from deploying the report and publishing it to the web.

RGB1 =
VAR R =
    SELECTEDVALUE ( 'Color 1'[R Dec] )
VAR G =
    SELECTEDVALUE ( 'Color 1'[G Dec] )
VAR B =
    SELECTEDVALUE ( 'Color 1'[B Dec] )
RETURN
    R & "," & G & "," & B

Check Out the Report

This post was an enjoyable combination of color, Power BI, and a bit of math. It was fun to make the report since it brought together my interests in accessibility and Power BI model optimization. At the least I’m hoping this gives you some exposure to how accessibility guidelines are applied to reports. If you are like me, you’ll find the color math fascinating and go down that rabbit hole.

Take a few seconds, pick some colors, and give the report a try.

Data Visualization, Microsoft Technologies, Power BI

Power BI Data Viz Makeover: From Drab to Fab

On July 11 at 3pm MDT, Rob Farley and I will be hosting a webinar on report design in Power BI. We will take a report that does not deliver insights, discuss what we think is missing from the report and how we would change it, and then share some tips from our report redesign.

Rob and I approach data visualization a bit differently, but we share a common goal of producing reports that are clear, usable, and useful. It’s easy to get caught up building shiny, useless things that show off tech at the expense of information. We want to give you real examples of how to improve your reports to provide the right information as well as a good user experience.

We’ll reserve some time to answer your questions and comments at the end. Come chat Power BI data viz with us.

You can register for the webinar at https://www.powerbidays.com/virtualevent/colorado-power-bi-days-2020-07-11/.

Come for the data viz tips, stay for the witty banter!

Data Visualization, Microsoft Technologies, Power BI

Data Visualization, Context, and Domain Expertise

I recently posted a graph to twitter and asked people to explain it.

Let’s look at the graph.

Bar chart showing low levels of steps in April until April 25th, when they increase about 3x and remain at that level through May.
Chart from Fitbit showing my step count from April 1 through May 23.

The graph is from Fitbit. It shows the number of steps I took each day between April 1 and May 23. We can see that I had a very low number of daily steps between April 1 and April 24. Then there is a spike where my steps almost quadruple on April 25. They decrease a bit for a couple of days while remaining well above the previous average. Then my steps increase again, staying up around 10,000 steps.

The Responses

The responses I received to my tweet largely fell into 3 categories:

  1. Complaints about the x-axis label
  2. Simple interpretations of the graph saying that the steps increased on April 25 and remained higher, often accompanied by statements that there isn’t enough data to explain why that happened.
  3. Guesses as to why the steps increased and then remained higher.

The X-Axis Label

Many of my twitter friends create data visualizations for fun and profit. It didn’t surprise me that they weren’t happy with the x-axis.

There are multiple x-axis labels that show the month and year, but the bars are at the day level. It’s unusual to see the Apr ’20 label repeated 4 times as we see in this graph. It’s not necessarily inaccurate, but its imprecision goes against convention.

The fact that multiple people commented on it demonstrates to me that it is more distracting than helpful. The way you format your data visualizations can be distracting. This is why I tweet and talk about bad charts and how to improve them for human consumption.

Literal Interpretation

Some people were only comfortable sticking with the information available in the chart. They acknowledged that the steps went up. Some said there were too many possible explanations to narrow it down to a certain reason why.

Speculative Explanations

I enjoyed the many guesses as to why my steps increased:

  • I suddenly got motivated to exercise more
  • I moved my office further from my bedroom
  • I’m building a really big staircase
  • The device used to track my steps changed
  • I started playing Just Dance every day
  • Covid-19 lockdown ended

A few people who know me (or at least pay attention to my twitter feed) had some insight.

I did get a new dog during the timeframe, but I got her on April 28th, not April 25th.

Also, the weather did warm up about 12 degrees Fahrenheit over the timeframe.

The Necessary Context

For the curious, here’s the real explanation.

I lost my dog Buster on April 4. He was with me for over 9 years, and he was my best friend. He was suddenly not feeling well at the end of March, and he was diagnosed with cancer. He declined rapidly, and I stayed with him on the living room floor until it was time to say goodbye. During those first 4 days of April, I really only left the living room to take Buster outside. I slept a lot that weekend and didn’t move much because I was sad.

With losing Buster, everything associated with Covid-19, and some other personal issues, I was depressed for the next few weeks. But I was also very busy with work. I had no energy to do anything else after work. And there wasn’t much to do since my city and state were on lockdown for Covid-19.

On April 25, I decided that the only way to get out of the emotional hole I was in was to get up and do something, so I walked a few miles around a nearby park. I came home and looked on PetFinder.com to see if there was a dog I’d like to adopt, and I came across a bulldog mix at Foothills Animal Shelter. I hadn’t cleaned my house since Buster died (see: depression). So I spent the rest of the weekend cleaning and dog-proofing just in case I brought the dog home.

On April 28, I adopted Izzy, an Olde English Bulldogge.

Izzy likes to walk. We walk between 2 and 4 miles each day. She is most of the reason the step count remained high throughout May.

Nice Dog. So What?

I hope what you’ll take away from this story is that to really deliver insights, you need to know the subject of your data visualizations. You need domain expertise. And it helps to have your own observations or other datasets to support the events you are visualizing.

If you don’t know me, any of the speculations could be the right answer. And the most you could do with my Fitbit data is to provide descriptive analysis, simply saying what happened without going into why. Many people who follow me on Twitter knew I recently got a dog. That explains the increase in step count from May 28 going forward. But it doesn’t address May 25th. Without the additional context of my step count in other months, you don’t know what my average step count is outside of this view. You wouldn’t know if my average count is normally closer to 3,000 or 10,000 because you don’t have that data. This is a perfect example of where you would need more data, more months of this data as well as additional datasets, to understand what is really going on. Sometimes there are actual datasets we can acquire, like weather data or Covid-19 lockdown dates. But there is no dataset for me losing Buster or struggling with depression.

This is part of why I prefer the term “data-informed decisions” over “data-driven decisions”. We often don’t have all the data to really understand what is going on. Technology has improved (see: Power BI) to make it quicker and easier to mash up data to provide a more complete picture. But we’ll still have to make decisions based upon incomplete data. If we have domain expertise, we may need to review data and ask questions to get better insights, and then rely on our knowledge and experiences to complete the picture.

This chart is also a good representation of a common issue in business intelligence: we often settle for only descriptive analytics. It may even have been a struggle just to get there. Let’s say I’m trying to become more active and using step count as a metric. You see this chart and see the increase in steps and say “That’s great. Do whatever you did last month to increase your steps even more.” Am I supposed to get another dog? Get less depressed?

Let’s pretend that my chart is not about my step count but is an operational report for an organization. That one chart tells you a trend of a single measure. We need more data, more visuals for this information to be impactful. The additional data adds necessary context. If this were a Power BI report, we might use interactivity to provide navigation paths to explore common questions about the data and to help identify what is influencing the current trend. Then you could use the report to facilitate a more productive conversation. I’m not addressing AI here, but after understanding the data and decisions made from it, you might introduce some machine learning to automate the analysis process.

Just having a report on something is not enough. The goal of data visualization is not to show off your data (if your service/product is data, that’s a different thing). It’s to help provide meaningful information to people so they can make decisions and take action. In order to do that, we need to understand our audience, the domain in which they are operating, and the questions they are trying to answer. Data visualization tools make it easy to get things on the page, but I hope you are designing your visualizations purposefully to facilitate data-informed decisions.

Consulting, Data Visualization, Microsoft Technologies, Power BI

Stress Cases and Data Visualization

Times are stressful right now. There is an ongoing pandemic affecting people’s health and livelihoods. Schedules are messed up, kids are home. People who aren’t used to working remotely are fumbling through learning how to work from home. And then there are the normal stresses that aren’t taking a break just because there is a pandemic: arguments with family members, home repairs, student loan debt.

Woman with her head in her hands
Life is stressful right now. It’s ok to not be ok.

I recently read the book Design for Real Life by Eric Meyer and Sara Wachter-Boettcher. I discovered it because I read another book by Sara Wachter-Boettcher, Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech that encourages us to look at the technology around us and consider how it can and has negatively affected people. If you work in analytics or web design, I recommend both books. She approaches design more from the context of user interfaces and web apps, but there is a lot of applicability to data visualization.

What’s a Stress Case?

Design for Real Life encourages us to consider stress cases. The idea behind stress cases is to consider our users as full, complex, sometimes distracted, vulnerable, and stressed-out people. They aren’t just happy personas who always click the right buttons and share all of our knowledge and assumptions.

Certain use cases, often labeled as edge cases, often go unidentified or dismissed as too infrequent. User interface designers, including data visualization designers, need to train ourselves to seek out those stress cases and understand how our design choices affect people in those usage scenarios. This helps us to minimize harm done by our design. But also, as stated in the book,

When we make things for people at their worst, they’ll work that much better when people are at their best.

Design for Real Life

There is a toxic trend in tech that we developers make things for ourselves, valuing the developers and designers over the users. Designing for stress cases helps us change that trend. We need to value our users’ time, understand our biases as designers, and make features that match our users’ priorities. A very applicable part of this for data visualization is to consider all the contexts that usage scenarios might happen.

Stress Cases in Data Visualization

Whether you are designing a visualization to be embedded in an app, included in an online news article, or published in a corporate dashboard, you can design for stress cases.

Let’s think about a corporate HR report built in Power BI that shows a prediction of employee retention. HR and team managers may use this information to help them assign projects or give promotions and raises. This dashboard and the conversation around it may address information related to identity (race, gender, sexual orientation). The use of the dashboard may affect someone’s compensation and job satisfaction.

How can we design for stress cases here?

We should be asking if we have the right (appropriate and validated) data to accomplish our goals, not just using whatever we can get our hands on. We definitely need to consider laws against discrimination that might be applicable to how we use demographic data. We need to consider the cost or harm done if we allow users to see these predictions down to the individual employee rather than an aggregation. And we should always be asking what actions people are taking as a result of using our dashboard. Have we considered any unintended consequences?

We want to use plain, easy to understand language. We want to explain our data sources and (at least high-level) how the predictive algorithm works. And we need to explain how we intend for this dashboard to be used. Basically, we want to be as transparent and easy to understand as possible. This dashboard can affect people’s livelihoods and happiness as well as the operational and financial health of the business. These data points are more than just pretty dots – they are people.

We also want to make sure our dashboard is easy to use. Think about digital affordances. We want it to be clear what happens when someone interacts with it. We can get fancy with bookmarks and editing interactions in a Power BI report. But does our intended user understand what is shown when they click a button that loads a bookmark? Can the intended user easily get what they need? Or do they have to jump through hoops to get to the right page and set the right filters?

Let’s say Sarah is a new manager at an organization that is trying to improve a high attrition rate, and she needs this information for a meeting with her boss and peers. She’s sitting in an online meeting using a 3-year-old tablet with 10 minutes of remaining battery life. Her two-year-old child is running around in the next the room. The group is discussing whether they should let some people go and then try to rebuild their teams. Can Sarah easily pull up the dashboard on her tablet and set the correct filters to see attrition numbers and retention factors for her team while trying to put on a brave face in front of her colleagues as she races against the tablet’s remaining battery time?

Visualizing the Coronavirus

Currently, it seems everyone in the data community wants to visualize the spread of COVID-19. Just look at the Power BI Data Stories Gallery. I get the appeal of using new and relevant data for practice, but consider your audience and the consequences of making it public. Do you trust and understand your data? Have you considered how the chart types and colors you choose can misrepresent the data? Who is it helping for you to publish your visualization out into the world? What message is your visualization sending? Is it unintentionally adding stress for your already stressed-out twitter followers? Most of us are not working with city officials or healthcare practitioners. We are visualizing this “for fun”. People are showing off Power BI/Tableau/D3 skills and not necessarily communicating clearly with purpose.

Your twitter friend/follower Frank is really concerned about the pandemic. His daughter lost her job at a restaurant. He’s worried about lining up projects for the next few months. And his wife is immunocompromised and in a higher risk group for getting COVID-19. He feels scared and helpless.

Your friend Dave is worried about his mother who lives alone a few hours away from him. He is bombarded by messages every day that say older people are more at risk of getting COVID-19. His mom says she is fine, but he wants her to come and stay with him. It’s all he’s thought about all day.

If you know nothing about epidemiology and don’t understand the response from various national, state, and local governments in your data, and you publish your viz with a choropleth (filled) map covered in shades of red, how will that affect Frank and Dave and everyone else who reads it? Did you add value to the COVID-19 conversation, or just increase confusion and fear?

Amanda Makulec published Ten Considerations Before You Create Another Chart About COVID-19 with some good advice, including the following.

To sum it up — #vizresponsibly; which may mean not publishing your visualizations in the public domain at all.

Amanda Makulec

Stress cases can be related to a crisis, mundane technology failures, or just situations that are stressful in the context of the user’s life. If you are visualizing data, remember there are people who may be interacting with our visuals in less than ideal circumstances. We need to design for them as much as for our ideal use cases.

If you have real-life examples of designing for stress cases in data visualization, please share them in the comments or tweet me at @mmarie.

Accessibility, Data Visualization, Power BI

PolicyViz Podcast Episode on Accessibility

I had the pleasure of talking with Jon Schwabish about accessibility in data visualization. The episode was released this week. You can check it out at https://policyviz.com/podcast/episode-169-meagan-longoria/.

Policy Viz
PolicyViz helps you do a better job processing, analyzing, sharing, and presenting your data.

If you’ve never thought about accessibility in data visualization before, here is what I want you to know.

  1. Your explanatory data visualization should be communicating something to your intended audience. You can’t assume people in your intended audience do not have a disability. People with disabilities want to consume data visualizations, too.
  2. We can’t make everything 100% usable for everyone. But that doesn’t mean we should do nothing. Achieving accessibility is a shared responsibility of the tool maker and the visualization designer. There are several things we can do to increase accessibility using any data visualization tool that don’t require much effort. Regardless of the tool you use, you can usually control things like color contrast, keyboard tab/reading order, and removing or replacing jargon.
  3. Accessible design may seem foreign or tedious in the beginning. We tend to design for ourselves because that is the user we understand most. But if we start adding tasks like checking color contrast and setting reading order into our normal design routine, it just becomes habit. Over time, those accessible design habits become easier and more intuitive.

I hope that one day accessible design will just be design. You can be part of that effort, whether you are a professional designer, a database administrator just trying to show some performance statistics, or an analyst putting together a report.

Listen to the podcast for my top 5 things you should do to make your data visualizations more accessible.

Conferences, Data Visualization, Microsoft Technologies, Power BI, SQL Saturday

New Power BI Report Design Pre-Con in 2020

I’m excited to announce that I will be offering a full-day pre-con about Power BI report design in the coming year called Bookmarks, brain pixels, and bar charts: creating effective Power BI reports. For a full session description and prerequisites, please visit the session page.

Screenshot of the eventbrite page for the pre-con at SQLSaturday Austin

I built this pre-con to help people better approach report design as an interdisciplinary activity where we are communicating with humans, not just regurgitating data or putting shiny things on a page. There are many misconceptions out there about report design. Some people see it as just a “data thing” that only developers do. Many BI developers avoid it and try to focus on what they consider to be more “hardcore data” tasks. I often hear from people that they can’t make a good report because they aren’t artistic. This hands-on session will dispel those misconceptions and help you clarify your definition of a good Power BI report. You will see how you can apply some helpful user interface design and cognitive psychology concepts to improve your reports. And you’ll leave with tips, tricks, and a list of helpful resources to use in your future report design endeavours.

Your report design choices should be intentional, not haphazard or just the Power BI defaults. We’ll review guidelines to help you make good design choices and look at good and bad examples. And we’ll spend some time as a group creating a report to implement the concepts we discuss.

Basic familiarity with Power BI is helpful for attendees. If you know how to add a visual to a report page, populate it with data, and change some colors, that’s all you need. If you feel like you lack a good process for report design to ensure your reports are polished and professional, this session will share an approach you can adopt to help accomplish your design and communication goals. If you feel like your reports are luckluster or not well-received by their intended audience, join me to learn some tips to improve. If you are a more experienced report designer and you want to learn some new techniques and see the latest Power BI reporting features, you’ll find that information in this session as well.

So far, I’m scheduled to present this session at two SQLSaturdays in Q1 2020:

SQLSaturday Austin – BI – February 7, 2020. Please register on Eventbrite.

SQLSaturday Chicago – August 14, 2020. Please register on Eventbrite.

SQLSaturday pre-cons are very reasonably priced. This is a great way to get a full day of training on a low budget! I hope to see you in Austin or Chicago.

Accessibility, Data Visualization, Microsoft Technologies

How a new custom PowerPoint template is helping us to be more effective presenters

DCAC recently had a custom PowerPoint template built for us. We use PowerPoint for teaching technical concepts, delivering sales and marketing presentations, and more. One thing I love about working at DCAC is that each of the 6 consultants is also a speaker at conferences. So we all care about making presentation content understandable and memorable.

In addition to the general desire to be an effective presenter, I have a special interest in accessible design. I speak and consult on accessibility in Power BI report design. So I feel a responsibility to try to be accessible in all areas of visual design. In addition, I know that making things more accessible tends to increase usability for everyone.

PowerPoint templates in general reduce manual efforts to assign colors, set fonts and font sizes, and implement other design properties such as animations. I’m all for making a decision once, templatizing it, and making it easy to instantiate. But most of the templates available within PowerPoint and sold online don’t follow good presentation design practices. That is to say, the formatting gets in the way of the content.

Having a template made

Anyone can make a PowerPoint template. You just have to learn how master slides work. Lots of marketing and graphic design companies offer to create PowerPoint templates. But they are mostly concerned with staying on brand or making something shiny. And people make presentations because we want to communicate information. I wanted our template to make it easy for us to follow some good design practices, including accessibility.

So I reached out to my friend Echo Rivera who has her own company, Creative Research Communications, that specializes in making visually engaging presentations about highly technical topics. I came across one of her tweets a couple of years ago and visited her website. Some of the things I have learned from Echo’s courses and blog posts include:

Echo worked with me to make a template that followed good design practices but was flexible enough for a variety of content and audiences. And we also made the template fairly accessible! I’m pleased with the way our template turned out. A template can’t do everything for you, but it can give you a good start.

The process of presentation template design

I found the process of designing the template interesting, so I thought I would share a bit about that.

First, I sent Echo some samples of the presentations we give and some ideas on a color palette. We met to discuss our corporate personality, our presentation needs, and our goals for the template. Then a few members of the DCAC team helped me pick some potential images for the title slide.

Next we picked icons and colors for sections that we thought we would commonly include in presentations. We stuck with a white background on some content slides to make it easier to use images and diagrams from online (so we wouldn’t have to expend effort removing image backgrounds when they weren’t transparent). It also made it easier to choose colors with good contrast.

Once we got the full draft of the template, the team reviewed it and tried it out on some slides. And because things were going too smoothly, we decided we didn’t like the image we selected for the title slide, and chose another one. We made a few adjustments to default font sizes so that slides would fit our company name and slide headings with long technology names on a single line. We also adjusted the position of the slide heading text on slides with the line and icon at the top (shown below) so the text didn’t sit directly on the line.

We made a version of the slide template that has a small single-color logo on each slide. I plan to use this for sales slides and other situations where we need to ensure our name is on a slide when taken out of context (like a screenshot of a single slide). But the logo is small and not distracting so it doesn’t negatively impact design.

We made the template expecting that team members would adjust the master slides and use the provided multi-purpose layouts as needed for each presentation. We will change icons and use blank slides to add diagrams and big images. We also have multiple options for title and thank you slides.

Benefits of our new PowerPoint template

There is a lot to the new template, and examples below are shown without a ton of background explanation. But I couldn’t write this blog post and not show some examples, and I didn’t want this post to turn into a novel.

Our slides use color contrast to create visual interest while staying close to our corporate color palette.

The spacing and font sizes allow for about 6 lines of text max in an all-text slide. Our default font size for text content is 32pt.

Content slide with large text and clean formatting
Content slide from Meagan’s presentation on accessible Power BI report design

We used icons and color to denote sections in our presentations.

I think the best thing that this process has done is encourage us to use less text and more images. Check out the recently created slides from one of John’s presentations below.

My checklist for accessibility in visual presentation design includes:

  • font sizes no smaller than 24pt
  • color contrast that meets WCAG standards (3:1 for large text, 4.5:1 for smaller text)
  • avoiding using color as the only means of conveying information
  • avoiding color combinations that are problematic for people with color vision deficiency

Echo worked patiently and diligently with me to measure and adjust colors to meet these criteria. It was great to have someone that understood these goals.

Feedback from other team members

To be honest, I think it took some time for the template to grow on people. But most of us have warmed to it. If you are used to small images, lots of text, and extensive use of clip art and smart art, switching to the template can be a bit difficult. But that’s kind of the point.

Echo gave us some videos on how to use the template and some slide makeover examples when she delivered the template, and I asked the team to watch this TEDx talk. That reinforced the design goals and choices.

I asked the team for comments, and this is what they said.

“I like having a professional-looking, themed template that isn’t just something out of the box that looks like everyone else’s. The template, plus the helpful background info force you to think about what you are puking onto a single slide. It will lead to some semi-major rewrite/re-evaluation of about every presentation I do.”

Kerry

“The template, in part with its notes and reminders, helps me to ensure that I put the proper amount of context on a given slide.  It’s a balancing act with font size and content.  If I have to reduce the font size below 32 pt and I still have content to provide, it goes on another slide.”

John

Final thoughts

Will every slide we make be perfect and beautiful? No. But this template will help us avoid common mistakes like having too much text on the slide, and it provides some built-in accessibility without us having to remember to make adjustments.

I really enjoyed working with and learning from Echo, and I recommend her for your presentation design needs. I want to note that she prefers that you take her training before she does custom design work for you so you have a mutual design foundation to build upon. But her courses are great, so that’s not a hardship.

It’s also a privilege to work with people that share and support my goals of effective presentation delivery and accessible design. PowerPoint templates are part of the branding and marketing collateral in an organization, and I love what this says about DCAC.

Data Visualization, DCAC, Microsoft Technologies, Power BI

Power BI for Communication and Marketing

We often focus on deep analysis and insights generated by machine learning when we talk about Power BI these days because it’s super cool and very fancy. But I think it’s important to remember that you can also use Power BI for simple communication of data. As humans, we are hard wired to process visual information faster than text alone. And it’s often more efficient and concise to convey information in a visual rather than text. We can show in one image what it takes paragraphs to describe. Outside of historical analysis and operational reporting, we can use data visualizations as an engaging way to convey simple facts in a communication or marketing effort. Many people do this with infographics.

Visualization can make simple numbers and facts more memorable and engaging. I enjoy using Power BI for this marketing communication purpose, so I made a report about the people I work with at Denny Cherry & Associates Consulting. I knew most of them before I started working at DCAC, so I was already aware that they were exceptional. But now you can see it, too, with our new Power BI report located at https://www.dcac.com/about-us/learn-more-about-us.

Screenshot of the home page of our About DCAC Power BI report

Data is some people’s preferred language. We can use it to discuss specific points as well as broader trends and comparisons. I have a sticker on my laptop that says “Please Talk Data To Me” for a reason. I can make sweeping statements about how my team is full of accomplished consultants, speakers, and authors. But it is much more impactful when you see the numbers: 27 Microsoft MVP awards and 8 VMWare VExpert awards over the years, a combined 113 years of experience with SQL Server, 86% of us having been a user group leader.

My Surface Pro tablet with a “Please Talk Data To Me” sticker on it

And because Power BI is interactive, you get to interact with my report, choosing which categories you want to learn more about. There is also a little guessing game built into the report. (Edit: Although there is currently a Power BI bug that I had to work around, so it’s helpful to know that the answers are limited to values 1-2500). But that is a blog post for another time, and for now you get a hint as to possible answers.) If I had just told you these stats, you might have listened, but you probably would have tuned out.

Our team even had fun browsing the report, seeing our collective achievements, and guessing who provided which answers.

Building the report

It was quick and easy to use Microsoft Forms to gather the data and then dump the responses to Excel. From there, I made a quick Power BI data model and put together my visualizations. The report is embedded on our website using a Publish to Web link. A few people have said they would like to do something similar for their organizations, so I’ll offer a couple of tips:

  1. Make sure the questions you ask aren’t violating any HR rules, and that employees know that some or all questions are optional. For example, I asked personal questions in the Fun Facts section about number of children employees have. This question was optional and our team felt comfortable answering it.
  2. Try to group your questions into categories so you can easily the separate sections and pages like I did. Then you can associate a color with each category.

If you do make something similar, I’d love to see it. Tweet me a link or screenshot at @mmarie.

Data Visualization, Microsoft Technologies, Power BI

Check Out the Updated Violin Plot Power BI Custom Visual

I wrote about the violin plot custom visual by Daniel Marsh-Patrick back in February. I thought it was a good visual then, but version 1.3 has recently been released with some nice enhancements.

First, the violin plot is now a certified custom visual. This means that it has been tested by the Power BI team to ensure it meets certain requirements, one of which is that the visual does not access external services or resources. You can be confident your data isn’t being sent externally when you use the violin plot.

As for the functional enhancements, a new legend has been added. This is a great addition to make the chart clearer and more easily read, especially for audiences that may not be familiar with how the violin plot works. The customizable legend calls out what markers are used for mean, median, and quartiles.

Violin plot with the new legend

Another good enhancement is the new column option for the combo plot. It allows you to have your plot show as a range column chart where the bar spans from the minimum value to the maximum value for each category. I chose to show only the mean and median in the example below, but you can also add quartiles.

Violin plot using the new column plot type

The barcode plot also has a nice enhancement in the tooltip. Now when you hover over a bar, you can see the number of samples with the highlighted value.

You can check out Daniel’s blog post to see the full list of enhancements for this release. Tweet me if you make something cool and shareable with the violin plot in Power BI.