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Category: Visualization

Accessibility in UI Design

Published 2024-02-26 by Kevin Feasel

Benedict Ampea-Badu shares some tips:

In this last segment of the series, we’ll delve into the crucial elements of navigation and flow, exploring further the part of web accessibility that ensures users can effortlessly navigate online content. Additionally, we’ll shine a spotlight on the indispensable practice of regular testing, an ongoing commitment that goes beyond compliance, providing invaluable insights into real user experiences and fostering continuous improvement.

Ensuring a seamless online experience for everyone and facilitating smooth navigation boils down to adhering to the fundamentals of web accessibility. It boils down to carefully planning how websites are laid out, making it easy for users to explore different things effortlessly. When developers grasp how users interact and tackle possible issues, they go beyond just ticking boxes on a checklist. Instead, they create websites that truly put users first, considering how people actually use and prefer to browse.

This is particularly about accessibility in web applications but many of the same principles apply to things like Power BI reports.

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Adding Superscripts and Subscripts to Axis Labels in R

Published 2024-02-22 by Kevin Feasel

Steven Sanderson changes the script:

Before we dive into the code, let’s quickly review what superscripts and subscripts are.

  • Superscripts: These are smaller-sized characters or numbers that appear above the baseline of the text. They are often used to denote exponents or indices.
  • Subscripts: On the other hand, subscripts are smaller-sized characters or numbers that appear below the baseline of the text. They are commonly used in mathematical expressions or chemical formulas.

Read on to see how you can generate these in R visuals.

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Adding Pagination to Bar Charts

Published 2024-02-13 by Kevin Feasel

Riqo Chaar turns the page:

Good User Experience (UX) design is crucial in enabling stakeholders to maximise the insights that they are able to derive from Power BI reports.  One common challenge of report design is effectively managing and displaying large datasets in bar charts without overwhelming the user. This article will describe the process behind a method that can mitigate this issue: adding pagination to bar chart visuals. This visual will provide the following functionality:

  • A number of categories filter: users can specify how many categories they would like to see per bar chart page
  • A page filter: users can navigate to different pages to see more categories

Click through to see how. I tend to prefer Power BI dashboards be glanceable, so pagination defeat that purpose to some extent. But so does having to scroll through a large list.

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Power BI Themes Gallery

Published 2024-01-29 by Kevin Feasel

Seth Bauer shares a tip:

Welcome to today’s tutorial where we’ll explore the Power BI Tips+ Theme Generator and its incredible features designed to streamline your Power BI report building experience. In this walkthrough, we’ll guide you through the process of getting started with the Power BI Tips+ Gallery, focusing on the Sunset theme. By the end of this tutorial, you’ll be able to effortlessly integrate our pre-configured Gallery Projects into your Power BI reports. It doesn’t get easier than this!

Click through for the process, including a video on how to do it.

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Fixing Low-Contrast Gradient Bar Charts in Power BI

Published 2024-01-24 by Kevin Feasel

Meagan Longoria looks at contrast:

Since conditional formatting was released for Power BI, I have seen countless examples of bar charts that have a gradient color fill. If you aren’t careful about the gradient colors (maybe you just used the default colors), you will end up with poor color contrast. Luckily there are a couple of quick (less than 30 seconds for most people to implement) fixes that can improve your color contrast.

Click through for a video demonstration and two tips from Meagan.

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Accessibility Guidelines for Apps and Visuals

Published 2024-01-16 by Kevin Feasel

Benedict Ampea-Badu shares some guidelines:

We live in the height of the digital age, where the digital space has become a thriving community, with every person craving a great yet personalized experience. In this era, there is one centralized truth with undeniable clarity: Accessibility is no longer a mere option; it is the cornerstone that will lead to the creation of a truly welcoming community.

In this second part of our series on accessibility design, we will discuss essential topics that lie at the heart of crafting accessible digital environments. We’ll begin by throwing more light on three of the five fundamental visual patterns vital to your designs:

  • Color Contrasting
  • Font Sizing
  • Labelling and Iconography

Read on for good information and plenty of examples.

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Visualizing Power BI Import Dependencies as a Graph

Published 2024-01-09 by Kevin Feasel

Chris Webb builds graphs, but not those types of graphs–the other type of graphs:

A few years ago a new pair of Profiler events was added for Power BI Import mode datasets (and indeed AAS models): the Job Graph events. I blogged about them here but they never got used by anyone because it was extremely difficult to extract useful data from them – you had to run a Profiler trace, save the trace file, run a Python script to generate a .dgml file, then open that file in Visual Studio – which was a shame because they contain a lot of really interesting, useful information. The good news is that with the release of Semantic Link in Fabric and the ability to run Profiler traces from a Fabric notebook it’s now much easier to access Job Graph data and in this blog post I’ll show you how.

Read on to see an example of it in action.

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Exploratory Data Analysis with F# and Plotly

Published 2023-12-26 by Kevin Feasel

Matt Eland is speaking my language (F#):

One of the most common tasks with data roles is the need to perform exploratory data analysis (EDA).

With EDA a data scientist, data analyst, or other data-oriented programmer can:

  • Understand the value distributions of their data
  • Identify outliers and data anomalies
  • Visualize correlations, trends, and relationships between multiple variables

Exploratory data analysis usually involves:

  1. Loading the data into a DataFrame
  2. Performing descriptive statistics to identify the raw shape of the data
  3. Visualizing variables of interest on their own or with other variables.

In this article I’ll walk you through the process of loading data from a sample dataset into a Microsoft.Data.Analysis DataFrame (the kind featured in ML.NET). Next, we’ll look at the descriptive statistics the DataFrame class provides and then explore the process of creating some simple visualizations with Plotly.NET.

Read on for the scenario and analysis.

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The Updated Stacked Bar Chart in Power BI

Published 2023-12-21 by Kevin Feasel

Tom Martens reviews an updated visual:

Personally, the stacked bar chart holds a special place in my heart when it comes to data visualization. It’s the tool I find myself using most frequently, which is why I decided to share a template using Deneb that I’ve been utilizing for a considerable amount of time: https://www.minceddata.info/2023/11/12/the-better-rectangular-pie-chart/

With the December 2023 release of Power BI Desktop, I can almost create the Deneb visual, which is fantastic as it eliminates the need for an additional custom visual. It’s important to note that while I’m a huge fan of Deneb, I also serve as the Power BI/Fabric sherpa in a large organization, and for this, I always try to reduce overall system complexity.

Click through for a fairly complex example of the visual.

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Data Modeling for Sankey Charts in Power BI

Published 2023-12-14 by Kevin Feasel

Marco Russo and Alberto Ferrari explain when Sankey charts can actually make sense:

Picture this: you manage a company that sells subscription services on the web, and you want to track the evolution of your customers by analyzing different events to understand how many customers start a trial before they purchase or how many renew or cancel their subscriptions.

The report should look like this: the darker flow indicates the number of customers who skipped the trial and went directly from a phone call to purchasing a subscription.

Read on for that sales funnel example and how you can prepare the data to make best use of Power BI’s Sankey chart visual.

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