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Visualization best practices

Best practices are key to developing informative visualizations that get your target audience into action. A dashboard has done its job when users can easily derive answers from it. Even beautiful dashboards with interesting data sources can prove useless if your target audience doesn't get any insight from them.

Think not only like an analyst, but also like a designer and user. Dashboards should contain interactive elements that are visible, predictable, and have a meaningful, logical layout with a simple design that makes complex decisions easier. Keep in mind that users typically do not have a priori idea of ​​what it takes to communicate with data clearly and effectively. Below are some links to white papers that you can include on your empowerment intranet:

Attached is a list of books by renowned data visualization experts. By adding these white papers and articles to the materials for your analytics community, you can add a deeper understanding and application of visualization best practices.

target group

The best visualizations have a clear purpose and are helpful for the intended audience. So you need to be clear about what you want to say and who you are saying it to. Does your target group know this topic very well or are they new topics? What kind of advice does she need? These are the questions you need to think about before you start designing so that you end up with a successful dashboard. For example, for executives, you will be more likely to provide aggregated summaries of data and KPIs rather than row-level transactions.

context

Make sure your views provide context. Titles, labels, individual units, and comments help your audience better understand your data views. Always try to tell stories with your data and graphs. As you do this, realize that there is more to a good story than just data, and consider the following:

  • Pay attention to aesthetics and always keep in mind that “attractive” often goes hand in hand with “effective”. In other words, a powerful view can generate an emotional response and lead to real communication with your target audience.
  • Style is important too. Make sure your views are consistent and easy on the eye. Your views represent you and what is important to you.
  • Dashboards that users can use interactively are engaging. With interactive elements, your target group can change the data, ask and answer questions and gain insights themselves. This promotes trust in your data.
  • Make your views lively and memorable. Pay attention to structure and context.

Chart selection

The choice of chart should be based on the question you want to answer or a specific insight you want to convey. You will almost always have to make compromises, as each diagram type has its own advantages and disadvantages. Always ask yourself whether the type of diagram you choose best conveys the message you want to convey and whether it is easy for your target audience to understand. The following table explains the types of graphs in the Show Me section of Tableau and how they can be used. It is best to post this table on your empowerment intranet for new user information.

diagram

description

Line chart - showing trends over time

Examples: stock price changes over a five year period, website page views during a month, revenue growth by quarter

Bar Chart - Compare data by category

Examples: number of shirts in different sizes, website traffic by site of origin, percent spend by department

Heat map - showing the relationship between two factors

Examples: segmentation analysis of the target market, cross-regional product launch, sales leads according to the individual representatives

Highlight table - Provides detailed information for heat maps

Examples: percentages of a market for different segments, sales figures in a certain region, population of cities in different years

Tree map - representation of hierarchical data as a proportion of a total

Examples: memory usage by computer, managing number and priority of tech support cases, comparing household budgets across years

Gantt chart - representation of duration over time

Examples: project timelines, duration of use of a machine, availability of players for a team

Bullet Chart - Evaluating the performance of a metric against a target value

Examples: sales quota assessment, actual expenses compared to budget, range of services (excellent / good / bad)

Scatterplot - Examining the relationship between different variables

Examples: susceptibility of men at a certain age to lung cancer compared to women, purchase patterns for smartphones by early adopters and latecomers, shipping costs for different product categories in different regions

Histogram - Understand the distribution of your data

Examples: number of customers by company size, student performance on exams, frequency of a product defect

Symbol Cards - Use these cards for totals rather than percentages. Proceed carefully as small differences are often hard to see.

Examples: Number of customers in different regions

Territory Maps - Use these maps for proportions rather than totals. Use sensible base regions.

Examples: Share of internet usage in certain regions, house prices in different city districts

Box-Whisker Charts - Representation of the distribution of a data set

Examples: Understanding the data at a glance, showing the data distortion at one end, identifying outliers in data

layout

How your target group “reads” a dashboard is not a trivial question. Your dashboard needs to guide the user's eye through a variety of views and tell the story behind each insight. It requires a meaningful "process" as well as a logical layout for the various information. A good dashboard design is one that lets users see what is happening and why, and what is most important. Think about how you will guide the user's eye through your dashboard. Are you pointing out where to look next?

You can take many suggestions for successful dashboards from design theory. Layout is a key component of any successful dashboard design. Here are some concepts to consider when creating visualizations:

  • Newspaper or Z layout - the most important content is placed either at the top or on the left in a visualization; users can find more specific content at the bottom right.
  • Empty areas - Use negative space (empty areas) and fills to demarcate sections in your visualization. Do not use wide "grid lines" like in a table.
  • Size - more important content (KPIs, summary visualizations, etc.) should be displayed larger than other items.
  • Device type - With device-specific dashboards, you can achieve the best visual experience on desktops, laptops, tablets and smartphones.

colour

Color is one of the most expressive aesthetic traits because it attracts attention. Color is the first thing that catches the eye. In this way, special findings can be emphasized concisely or outliers can be made perceptible. However, color should not be used indefinitely as a design resource.

The effective use of color is central to creating high quality data visualizations. Color types (warning vs. highlighting), creating custom color palettes, and ensuring consistency are important aspects to consider in your standards.

Proper use of color is critical to creating coherent and impactful data stories. Here are the key factors to consider for any successful dashboard:

  • Color Choices - The base colors that will make up most of your design should be neutral colors. Techniques such as grayscale can help you maximize the possibilities for contrast and the visibility of your data-driven points. The expanded colors - for accents, highlights, and warnings - should reflect the brand. Use expanded colors sparingly to draw attention to key messages in the data.
  • Color Types - Think about the best time to use sequential, diverging, category-based, highlighting, or cautionary color themes.
  • Custom color palettes - Create your own company palettes to create homogeneity and give new users orientation.
  • Consistency - Check your visualizations several times to make sure a color (e.g. red) doesn't have different meanings. Identical and repeated colors can suggest a relationship that doesn't even exist.
  • Accessibility - When designing, keep color blind users in mind.

Title and Subtitle

Titles are an easy way to make your dashboard more understandable for your audience. Use subtitles e.g. B. to describe the interactive use of the worksheet or dashboard. Titles and subtitles are a powerful and easy way to make dashboard navigation easier. The following example draws the audience's attention to the question and then explains how to use the dashboard to answer that question.

Effective titles and subtitles

Likewise, by changing the filter title to more intuitive text, you can guide the viewer through interacting with a dashboard.

Example of a filter


Tooltips

Tooltips support the target group by highlighting important information. In the following example, the county and state are highlighted in bold and a different color. This way, the scatter plot does not need to be broken down any further. The important related dimensions and measures are indicated in the tooltip. This saves space and prevents the dashboard from becoming cluttered, so your viewers can focus on insights instead of having to interpret the visualization.

Effective tooltips

If viewers notice something interesting in the tooltip, they can use the tooltip interactively. Associated markings and outliers are then highlighted in the visualization.

Formatting a tooltip

Fonts

Typography is an important factor. It may be tempting to use lots of fonts and sizes on one dashboard. However, this is not advisable. Rather, establish a clear hierarchy for your typography. The following example uses a separate font for the top, middle, and bottom levels. The font color for the middle layer is blue to attract the viewer's attention. Color can be used to highlight the most important information (which, by the way, does not necessarily have to correspond to the top level).

Upper, Middle, and Lower Level Fonts (Courtesy of "The Big Book of Dashboards")

Choose the font so that it underlines the visual hierarchy in your visualizations through size, bold formatting, color, and font.

  • Size - Larger elements convey importance because they attract attention. Use the largest fonts for KPIs, titles, etc.
  • Bold Formatting - Elements formatted in bold also convey importance because they are eye-catching. You can also vary the bold formatting in the visualization in connection with the size. For example, you have the option of using a 24-point font for both the title and the KPIs. If you now also format the KPIs in bold, they will immediately attract the attention of your target group.
  • Color - In general, it makes sense to stick to shades of gray and black for titles, texts, and KPIs. You can also highlight KPIs in color, but you should coordinate this color with the other colors in your visualization. The eye is drawn to darker colors, so it is advisable to make titles lighter so that they do not distract from other elements.

Dashboard size

By default, Tableau dashboards are set to a fixed size. If you keep this setting, make sure that your visualization is built to the size you want it to be displayed. You can also set “Size” to “Automatic”. Tableau then automatically adjusts the overall size of a visualization to the screen size. For example, if you create a 1300 x 700 pixel dashboard, Tableau will resize the dashboard for smaller displays. This can sometimes lead to compressed views or scroll bars. This can be avoided with the range adjustment feature.

Dashboard size range

If you work with Tableau Desktop, you can also create dashboards tailored to specific device layouts. On tablets, for example, your dashboard will contain a different set of views and objects than on smartphones. To do this, see Create Dashboard Layouts for Different Device Types.

Dashboard interactivity

When creating dashboards, you must always keep an eye on your target audience and consider how you are communicating that the dashboard can be used interactively. Seasoned users know they can click and experiment, but new users may not have the knowledge or confidence to do so. Your job now is to help ensure that such decisions are made consciously and not accidentally.

Every form of interactivity must be recognizable for your respective target group - e.g. B. subtitles with information that further information can be displayed by clicking on a certain point or by pointing the mouse pointer over it. Filters, tooltips, and actions add interactivity to your data. Filters are the most obvious way to interact with a dashboard. Users can also interact with visualizations by selecting markers or hovering over them to display tooltips. The actions you specify allow users to navigate and make changes in the view. The following table shows the options for equipping dashboards with interactivity.

Type

description

Highlighting and highlighting actions

  • Easily find interesting data without changing the context
  • Show other marks with the same attributes
  • Find related data in different sheets

Filters and filter actions

  • Focus on the data to be analyzed
  • Control the data context
  • Show relevant data and remove unnecessary data

parameter

  • Investigate what-if scenarios
  • Customizing views
  • Improve the flexibility of dashboards

Sentences and Set Actions

  • Dynamic updating of the parts of a sentence
  • Compare parts with a whole
  • Seamlessly drill down through hierarchies
  • Updating a calculation through interactive use of data

Tooltips

  • Providing details as needed
  • Avoid cluttering dashboards
  • Insert a visualization in a tooltip

Url actions

  • Integration of external content in a dashboard
  • Provide more detailed information when needed
  • Direct users to websites

Dashboard navigation

  • Guide users through workbooks
  • Direct users to more content

When creating dashboards, consider how and why you are incorporating interactivity. The following questions provide support for this:

  • Why does a viewer have to use the dashboard interactively?
  • What additional insights can be gained through interactivity?

Design to ensure performance

Performance here means the speed at which you can work in Tableau. This can affect the speed of data analysis, for example if you work with large company databases via slow remote access. Or the term refers to the time it takes to load a view or dashboard that you access on your desktop PC or on Tableau Server or Tableau Online.

Performance and efficiency should be considered at the design stage - and not afterwards. The speed of reaction is an important success factor for end users in connection with the use of reports and dashboards. When your workbooks are viewed quickly and changes are responded to quickly, you keep your users happy.

Several factors make a workbook "efficient". Some of these factors are technical and some are more user-oriented. In general, the following properties are important for an efficient workbook:

  • Easy - Is the workbook easy to create and will it be easy to maintain in the future? Does it use the principles of visual analysis to clearly convey the author's message and the data?
  • Flexible - Does the workbook answer multiple questions from the user, or just one? Does it create an interactive experience for the user or is it just a static report?
  • Fast - Is the workbook responding fast enough for the users? This can refer to the time it took to open or refresh the workbook, or to responding to an interaction. While this is a rather subjective aspect, in general workbooks should provide an initial display of data and respond to user input within a few seconds.

The performance of a dashboard is affected by:

  • The visual design at both the dashboard and workbook level - i. H. how many elements, how many data points are there, how can filters and actions be used, etc.
  • The calculations - e.g. B. what type of calculation is used, where is the calculation performed, etc.
  • The queries - e.g. B. How much data is returned, is it SQL, etc.
  • The data connections and underlying data sources.
  • Differences between Tableau Desktop and Tableau Server or Tableau Online.
  • Other environmental factors, such as hardware configuration and capacity for Tableau Server.

For more information, see the How to Design Efficient Workbooks white paper.

Accessibility

To help as many users as possible have access to your views - or if you work in an environment that is subject to US Section 508 or other accessibility laws and regulations - you can use Tableau to create data views that comply with the Web Content Accessibility Guidelines (WCAG 2.0 AA) are sufficient. This includes views that users can access through speech output, braille keyboards, keyboard-only navigation, and so on. For more information, see Creating Accessible Views of Data.