This is the first part of a three-part series that describes the connection options for the SAS Viya SDK for JavaScript. Overview (this article!) Direct Connection Report Packages   SAS provides a set of software development kits (SDKs) that help developers embed insights and content from SAS Viya into custom dashboards, portals, and web pages. A software development kit is a set of tools that help developers create software or apps for a specific platform, operating system, computer system, or device. An SDK can contain libraries, APIs, utilities, sample software, technical notes with documentation, code samples, or tutorials. SDKs enable developers to create content that will work with a specific environment.   The SAS Viya SDK for JavaScript is a collection of JavaScript libraries that allow you to embed insights and content from SAS Viya into custom dashboards and portals. The SDK is comprised of three libraries: Authentication Library: sas-auth-browser Content Components Library: content-components Report Components Library: va-reports-components   The Authentication Library The authentication library (sas-auth-browser) provides an API that ensures that a user is authenticated before making SAS API calls or using SAS web components. This library is needed to use both the content components library and the report components library in the SAS Viya SDK for JavaScript. For examples on how to use the authentication library to connect to SAS Viya, see https://github.com/sassoftware/sas-viya-sdk-js/tree/main/sdk/sas-auth-browser.   The Content Components Library The content components library (content-components) is a JavaScript library that enables users to navigate, preview, and open content in SAS Viya from custom web pages and applications. Users can browse items in SAS Viya folders and, when integrated with the report components library, can display reports from SAS Visual Analytics. When using the content components library, you also need to access the authentication library to ensure user authentication. This is a useful library to use to build your own interface that can directly integrate with and navigate through SAS Viya content. For documentation and examples on how to use the content components library to create tiles representing SAS Viya content items, see https://github.com/sassoftware/sas-viya-sdk-js/tree/main/sdk/content-components/examples.   The Report Components Library The report components library (va-report-components) is a collection of JavaScript libraries that can be used to embed SAS Visual Analytics content in your custom web pages and applications. The report components library calls the authentication library implicitly, so there is no need to access the authentication library in your code. You can use the provided framework to embed an entire report, pages from a report, or individual graph objects from multiple reports to give your consumers a completely unique, innovative, and customized experience. Users can even drive interactions and filters on SAS visualizations using other Visual Analytics content or using interface elements included in your web page or application. Using the power of SAS Viya, this library enables you to seamlessly integrate your specific design requirements with a wide range of analytics and insights delivered by SAS Viya. For documentation and examples on how to use the report components library to embed Visual Analytics report content, see https://github.com/sassoftware/sas-viya-sdk-js/tree/main/sdk/va-report-components.   Methods of Embedding Content In this series, we will focus on the report components library, which can be used in two fundamentally different ways: online using a direct connection to SAS Viya or offline using SAS report packages. Each method has its benefits and limitations, which will be discussed in future articles. The method you choose may depend on many factors, including your organizational policies, the features and functionality you want to include in your web page, and the types of configurations you want to make in your environment.   In the next part of this series, we discuss the requirements, the steps, and the details of using the report components library by connecting directly to SAS Viya.   References Documentation: SAS Visual Analytics SDK Documentation: SAS Content SDK Examples: sas-auth-browser Documentation and Examples: content-components Documentation and Examples: va-report-components ... View more

Watch this Ask the Expert session to learn tips and tricks to ensure your reports are both useful and compelling.   Watch the Webinar   You will learn: The steps for creating impactful reports. How to apply report design best practices. How to choose the best chart type for your data. The questions from the Q&A segment held at the end of the webinar are listed below and the slides from the webinar are attached.   Q&A What if I don’t know which type of chart to use for my data. Can SAS Visual Analytics help? If you recall, the first thing I did was change the treemap to the object that Visual Analytics recommended to use. So, by default, based on the data items you assigned to the object, Visual Analytics will make a recommendation on the chart type to use. If you don't know what type of chart to use and you're building a chart from scratch, you can take the data items you want to visualize and drag them to a page; Visual Analytics will select the best chart type based on the data items selected. This is a great place to start, and then you can modify the chart type as necessary, just like we did in the presentation.   How can I apply my corporate colors to a report? At the report level, options are available for modifying the report, like setting the theme or the colors used to display the report. There are different themes that are available by default. In addition to these default themes, you can also create your own, which can be based on your corporate colors. Once you have the ability to create themes, only certain users can do that, and those themes are applied and pushed out for everybody to view, they will be listed under Theme and you can apply them to your report. As you select different themes, all the objects in the report are updated to use the colors and styles associated with that theme. One nice feature of these report-level themes is that for each object, if I use the default or automatic colors, changing the theme will automatically change the colors in the objects to use whatever is specified in the theme. That's another reason why you would want to use the defaults over assigning your own.    I want to create a landing page for my report. Is there any templates or shapes to design it manually? In the presentation, the Table of Contents page was a template that I created specifically as a landing page for all my reports. This specific template uses only images and text objects, but you can add any objects that are available in Visual Analytics. It might be a good idea, depending on your audience, to use something like a video that shows how to navigate the report or has someone on screen describing the report and the purpose of it. I always think it's nice to have that personal touch and see someone actually work with the report. First, you create your page using whichever objects you want (in whatever arrangement you want), then create a template by selecting the Options button on the page tab and selecting Save page template. Once the template is created, you can use it in other reports, so they all look about the same.   Can the SAS Graphics Accelerator be used with this kind of report? Yes. The SAS Graphics Accelerator enables users with visual impairments or blindness to create, explore and share data visualizations. It supports alternative presentations of data visualizations that included enhanced visual rendering, text descriptions, tabular data, and interactive sonification.  Sonification, the ability to present data by using sound, is available for some object types in Visual Analytics. Visual Analytics provides sonification through the SAS Graphics Accelerator. For more information about how to build accessible reports, see "Creating Accessible Reports in Using SAS Visual Analytics" in the SAS Visual Analytics documentation.   What is the cost of using SAS Visual Analytics tool? For more information about accessing a free trial or purchasing SAS software, visit How to Buy SAS Software.   Where can I find Orion star data? Some sample data can be found at the SAS GitHub repository - sas-viya-quick-start.   Recommended Resources Beautiful Reports Creating Accessible Reports Using SAS Visual Analytics Envisioning Information by Edward Tufte Gallery of SAS Visual Analytics Objects Telling Your Data Story by Atrin Assa Tips and Techniques for Designing the Perfect Layout with SAS Visual Analytics by Ryan Norris and Brian Young Tips for Building Rich Interaction in Your SAS Visual Analytics Reports by Jeanne Marie Tan and Sierra Shell SAS Visual Analytics Stories are Data with a Soul by Ted Stolarczyk The Visual Display of Quantitative Information by Edward Tufte Types of Charts: Choose the Best Chart to Convey Your Message Visual Explanations by Edward Tufte Please see additional resources in the attached slide deck.   Want more tips? Be sure to subscribe to the Ask the Expert board to receive follow up Q&A, slides and recordings from other SAS Ask the Expert webinars. ... View more

This is the sixth part of a six part series that describes tips and tricks for building impactful reports in SAS Visual Analytics.   Draft a Plan Choose the Best Chart Bonus: Chart Best Practices Focus on What’s Important Consider the Layout Test, Test, and Test Again (this article!)   SAS Visual Analytics enables you to create compelling, interactive reports that can be viewed by anyone, anywhere. To create impactful reports that resonate with your audience you need to (1) draft a plan for the report, (2) choose the best chart type to display your data, (3) create your reports so viewers can focus on what’s important to them, (4) pick a layout that will best display your data and tell your data story, and (5) test the report to ensure it operates and looks the way you want. In this post, we will focus on the last step in the process: Test, Test, and Test Again.   In this step, you need to test your report to ensure that everything works the way you intend it. This can range from evaluating the performance of the report, to conducting a peer review, to testing on multiple devices, screen sizes, and displays. In addition, more tests may need to be performed depending on how the report will be used (like creating a PDF, printing the report, projecting the report, embedding report elements in a custom web page, viewing the report from SAS for Microsoft 365, playing the report, or viewing the report using a browser with a different locale).   Use the Report Review Pane To start, use the Report Review pane to evaluate the performance and accessibility of your report. This pane incudes a list of issues categorized by severity (low, medium, and high), a description of each issue, and suggestions for improvement.     The Report Review pane can be accessed from the left pane in SAS Visual Analytics when you are editing the report. The Report Review pane will note the performance issues, like the following:   If the data source contains many calculated items. Consider reducing the number of calculated items or calculating the values in the data preparation phase, if possible. If the report uses nested containers. Consider adjusting the layout of the report to avoid the use of nested containers. If a page contains too many objects. Consider reducing the number of objects displayed on each page. Recall that pages with fewer than 7 objects are easier for users to interpret.   For a full list of performance issues, see “Report Review Pane Reference” in the SAS Visual Analytics: Reference documentation.   These performance improvements can be especially useful for users who view the report on a mobile device.   The Report Review pane will also note accessibility issues, like the following:   If the report contains color-dependent display rules. Color-dependent display rules might not be accessible for users with color blindness or other visual impairments. If color-dependent display rules are used, provide another object that includes the information presented by the display rule. If a page contains linked selection actions. Screen reader users cannot perceive linked selection actions between objects or data elements in the report. If objects in the report do not have meaningful names. All objects need meaningful, accessible names for assistive technology. It’s a best practice to add your own meaningful names rather than using the default name.   For a full list of accessibility issues, see “Report Review Pane Reference” in the SAS Visual Analytics: Reference documentation.   Pro Tip! Provide meaningful titles and names for all objects and pages in your report. Alternatively, you can specify alternative text for objects, which will be read by screen readers.   Conduct a Peer Review Next, ask colleagues for feedback on your report. Ask them the following questions:   What is the data story? Is the report easy to navigate? Did you get lost? Did all the actions work? Were all the features of the report apparent?   Then, use their feedback to make your report even better than it was before!   Test on Multiple Devices Test your report on various devices and screen sizes. You can do this by using the Developer tools for your browser and clicking the Toggle device toolbar button. This enables you to view and navigate the report using different devices and screen sizes. This is especially important if the precision container is used in the report as the objects can be displayed in an unusual manner on different screens.     In Chrome (pictured), click the Customize and control Google Chrome button in the upper right corner of the web page and select More tools > Developer tools. In Edge, click the Settings and more button in the upper right corner of the web page and select More tools > Developer tools. In Firefox, click the Open application menu button in the upper right corner of the web page and select More tools > Web Developer Tools. Then click the Toggle device toolbar button to choose a device.   Create a PDF If the report will be shared via report distribution, you should create a PDF of the report by clicking the More button and selecting Export > PDF. The PDF can include page numbers, a table of contents, appendix information, details tables, a cover page, and accessibility tags. In addition, you can click the Use page size button to create a PDF based on the current size of your browser window.     The Export PDF window enables you to specify options for the document and select the pages and objects to include in the PDF.   Perform a Test Print If users will be printing hard copies of the report, perform a test print. You can also print the report in grayscale to ensure that users with color blindness can identify color differences.   Project the Report If the report will be projected for a presentation, perform a test run to ensure the colors show up how you intended and have sufficient contrast.   Pro Tip! Users can invert the application colors of the report (by pressing Ctrl+` on the keyboard) or override the report theme by selecting the Override the report theme and use the SAS High Contrast report theme setting in the SAS Visual Analytics > Themes settings window. If your audience is likely to view the report using one of these methods, you should test them out to ensure all the report content is viewable and readable.   Embed the Content in a Custom Web Page If the report content will be embedded in a custom web page, view the report using the SAS Viya SDK for JavaScript. You can do this by generating a SAS report package and viewing package contents. Report packages can be generated by clicking the More button in the upper right corner of the report and selecting Export > Report package. The report package includes a file (index.html) that will enable you to view the report content on a custom web page.     The Export Report Package window enables you to select the content that will be included in the SAS report package. You can also save the report package to SAS Content.   Access the Report from SAS for Microsoft 365 If the report will be accessed from Microsoft Office products, use SAS for Microsoft 365 to ensure the report appears how you expect and to verify that all actions and links work as intended.   Play the Report If the report will be presented on a kiosk or a slide show, play the report by accessing the report in View mode, clicking the More button in the upper right corner of the report, and clicking Play report. You can modify the speed, playback time, and display by clicking the More button in the upper right corner of the report and clicking Edit playback.     The Edit Playback window enables you to modify the speed and display of the playback.   View the Report Using a Different Locale If the report has been localized, you might want to view the report using browsers with different locales. This will ensure that the localization was completed and is applied successfully.   Pro Tip! If you choose to localize reports, make sure to localize all available text. This helps avoid problems that will arise if the report contains mixed-language content.   Summary After you have drafted a plan for your report, selected the best charts to display your data, enabled your viewers to focus on what’s important, and considered the layout of each page, the last step is to thoroughly test your report. At a minimum, you should analyze the performance and accessibility of the report using the Report Review pane, conduct a peer review, and view the report on different screen sizes. Then, you should perform other tests as necessary for your use case.   References Beautiful Reports   Tips and Techniques for Designing the Perfect Layout with SAS Visual Analytics by Ryan Norris and Brian Young   Documentation: Keyboard Shortcuts for SAS Visual Analytics   Documentation: Viewing Objects with SAS Graphics Accelerator   Documentation: Creating Accessible Reports Using SAS Visual Analytics   Documentation: Accessibility Features for SAS Visual Analytics   Documentation: Report Review Pane Reference     Find more articles from SAS Global Enablement and Learning here. ... View more

This is the fifth part of a six part series that describes tips and tricks for building impactful reports in SAS Visual Analytics.   Draft a Plan Choose the Best Chart Bonus: Chart Best Practices Focus on What’s Important Consider the Layout (this article!) Test, Test, and Test Again   SAS Visual Analytics enables you to create compelling, interactive reports that can be viewed by anyone, anywhere. To create impactful reports that resonate with your audience you need to (1) draft a plan for the report, (2) choose the best chart type to display your data, (3) create your reports so viewers can focus on what’s important to them, (4) pick a layout that will best display your data and tell your data story, and (5) test the report to ensure it operates and looks the way you want. In this post, we will focus on the fourth step in the process: Consider the Layout.   You should try to arrange your reports in a way that makes sense for your data story. In general, follow these best practices:   Limit the number of pages Limit the number of objects Make more important objects larger Consider the placement of objects Arrange objects with actions in a logical order Use negative space Use the default grid layout or containers   Limit the Number of Pages If you need more than 6 or 7 pages to tell your data story, consider breaking the story into multiple reports. Fewer pages make the report seem less complex and makes it easier for viewers to remember the content presented on each page. Limiting the number of pages can also help improve the performance of the report (especially if the report is viewed on a mobile device).   Be sure to arrange the pages to advance your data story. Consider adding a table of contents page with links to each page for easy navigation or adding an introductory page with useful information (like the company logo if required, the data update schedule, contact information, or a summary of the report).   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   In this example, pages are arranged in a logical order that advances the data story. The order in which the pages are presented give the viewers a suggestion on how to access the pages: Table of Contents > Draft a Plan > Choose the Best Chart > Focus on What’s Important > Consider the Layout > Test, Test, and Test Again. In addition, each page has a descriptive name that describes one part of the data story.     In this example, a page is created to function like a Table of Contents for the report. It has the name of the report on the left. On the right, there are instructions for accessing each page, a list of pages with links to each page, details about the data source, and contact information for the report designer.     In this example, a page is created to function like an introductory page. The name of the report is presented along the top (along with an image relating to the company). On the left is an overview of the report and a link to a details page that describes the actions in the report and how to use them. On the right is the update schedule for the report and data, the date of the last update, and contact information for the report designer.   Page links can be used within the report to control navigation or to provide additional details (like with a pop-up page). Using page links for navigation as opposed to page tabs can reduce the chance of overwhelming users with too many details up front. In addition, using page links can also help with accessibility by providing alternative views of the data.   Limit the Number of Objects Each page should contain a limited number of objects (between 2 and 6). This enables viewers to focus on the data and can improve comprehension of the page. In addition, limiting the number of objects can help improve the performance of the report as each page loads separately.   Make More Important Objects Larger You should enhance visibility of your report and direct the viewer’s attention to the main point of the story by making more important objects larger on the page and less important objects smaller. The larger the graph or chart, the more time the audience will spend studying it.     In this example, the geo map is the largest object on the page as that is what the viewer should focus on first. The key value objects provide additional details about the selected area and are much smaller than the geo map and the same size as each other. This indicates that they are less important than the geo map, but equally important to the other key value objects. Lastly, the drop-down list control takes up minimal space and spans the top of the report indicating it has some relationship to the other objects. In this case, a viewer can choose a country to filter the geo map and the key value objects.   Pro Tip! Once you have created pages that meet your specifications, you can save them as a page template and reuse them in other reports, which will speed up development time in the future. To save a page as a page template, right-click the page tab and select Save as page template. You can save as many page templates as you want, publish them for other users (if you have the appropriate permissions) and create a thumbnail image of the page to easily identify it later. Be sure you give the page template a meaningful name.   Consider Placement of Objects The placement of objects on the page is also important. Placing an object in the center of the page or in the top, left corner can create a focal point. This placement, however, can differ based on the location of the audience. In cultures that read from right to left, placing an object in the top, right corner will create a focal point.     In this example, for cultures that read left to right, the section on the left is noted first, then the needle plot in the center of the report, and lastly the list table at the bottom of the report. By placing objects in a specific order, you can direct your viewer’s progress through the page.     In this example, two columns of objects are displayed: the column on the left shows details about South America and the column on the right shows details about Europe. In addition, by placing the key value objects on one row and the bar charts on the next row, the viewer can intuit that those objects should be compared.   Arrange Objects with Actions in a Logical Order If your page contains objects that use actions, arrange the objects on the page in a logical order. For localities that read left to right, the source object should be placed in the upper left corner and target objects should be arranged to the right of and below the source object. Be aware that this arrangement will be different for cultures that read from right to left.     In this example, the source object (the list control) is placed in the upper left corner. Selecting a country in this object will filter the information displayed in the other objects on the page. In the upper right corner is the geo map, which filters the objects in the lower half of the report. The objects on the bottom have a linked selection action defined, which enables viewers to click a bar or row and highlight the associated data in the other object.   Use Negative Space Negative space can be used to increase comprehension of the report and enable easier navigation. It also makes for a more visually appealing and elegant report. To increase negative space, avoid adding borders and add margins and padding to objects. As you add margins and padding, remember to be consistent.     In this example, the report on the right contains no negative space. Objects are displayed side by side and on top of each other. This makes the report appear cluttered and can make it difficult for viewers to focus on the details. The report on the left, on the other hand, uses default padding around report objects to provide a buffer. This enables viewers to focus on one chart at a time to fully absorb the information.   Pro Tip! Use caution when modifying the padding for objects from the default. Larger amounts of padding can crowd report content when the report is viewed on small screens or when the zoom is set above 100%. If you modify the default padding, be sure to test the report thoroughly to ensure the content looks how you intended.   Use the Default Grid Layout or Containers You can use the default grid layout or containers to organize the content on each page.   The default grid layout (4x8) enables you to place objects directly next to other objects with no overlap. All objects on the page are sized to fit on the user’s screen. When you adjust the size of one object, the other objects on the page automatically resize to fill the entire screen.   Alternatively, you can use containers to group objects and provide additional layout options. The prompt container can be used to organize multiple prompts in the report prompt area, the page prompt area, or on the canvas. Using this container saves space in the report and makes it easier for mobile device users to navigate the report. It enables viewers to expand the container to view and modify prompts and collapse the container to view the page content.   The (vertical) scrolling container enables you to create a report that functions like a web page. You can add more information to the page and the charts can be larger. This can improve the viewing experience on a mobile device and enables more clarification of objects because you have space to add text next to each object with a description or additional information.   The stacking container displays objects as if they are in a slide deck, one at a time. This can be used to group related objects. The stacking container can also provide an alternative way to view the same information in a different fashion, like by including a table that presents the information displayed or by including a more mainstream chart. Including alternative views of the same information helps improve the accessibility of the report, especially for users of screen reader technology.     In this example, the prompt container is used to group several control objects (a button bar, a drop-down list control, a list control, and a text input control). The vertical scrolling container displays the content like a web page. Using this container, you can scroll down to view more information and make graphs larger than the page. The stacking container offers an alternative way to display additional details or display the same data using another, more accessible chart type.   Pro Tip! Avoid precision containers as they can cause problems when reports are viewed on different screen sizes. If you do use precision containers, it’s recommended to set the report-level option Set fixed report size to specify a fixed size for the report. If you use this option, however, be sure to test your report on all screen sizes.   Summary After you have drafted a plan for your report, selected the best charts to display your data, and enabled your viewers to focus on what’s important, you need to consider the layout of each page. As a best practice, you should limit the number of pages and objects and layout objects to direct the viewer’s focus to your data story.   In the last part of this series, we discuss testing the report.   References Beautiful Reports   Tips and Techniques for Designing the Perfect Layout with SAS Visual Analytics by Ryan Norris and Brian Young   Tips for Building Rich Interaction in Your SAS Visual Analytics Reports by Jeanne Marie Tan and Sierra Shell     Find more articles from SAS Global Enablement and Learning here. ... View more

Watch this Ask the Expert session to learn how you can create beautiful interactive reports that help convey your message.   Watch the webinar   You will learn: The steps for creating effective reports. How to choose the best chart type. Best practices for creating reports quickly and easily.   The questions from the Q&A segment held at the end of the webinar are listed below and the slides from the webinar are attached.   Q&A If you have a lot of information, is it better to have a longer page (so user would have to scroll down to see the whole report) or have multiple tabs (so the user doesn't scroll but clicks across the tabs instead). I'm thinking of website reports/dashboards rather than something that is more of a presentation. It really depends on your audience. Remember, whenever we think about adding things to different pages, we want each page to stand on their own. If there's information that you need your viewers to know to understand other parts of the page, I would recommend using a scrolling container and making a longer page that has those details rather than them having to remember it and jumping to a different page. Now you can always provide additional details with links as well. For example, let's say that I'm showing a Geo map that has all of our customers, and I want to focus on a specific subset of customers and see details about them. I can link to another page that has details about that set of customers that I've selected instead of displaying it all on a single page. Both solutions are valid. It just depends on what exactly you're trying to convey. You'll want to think about, do the viewers need to remember something to understand what's presented in a different page? If so, consider adding those details to that page so they don't miss the message. In addition, you'll want to think about if there is any way that you can limit the information displayed on the page by providing links to a page with additional details.   On the "Consider the Layout" page referring to the Table of Contents, can you show where you get the text box designs for the layout of the table of contents?  For example, you have circles with expanded borders for the text. Is that in SAS Viya? Both of the Table of Contents pages were created using a mix of images and text objects. You can use background colors to distinguish between the different text objects. In addition, you can create a layout of images and text in PowerPoint (as is done in one of the examples in the presentation), take a screenshot of the layout, and add it as an image in Visual Analytics. You can also add text with links to the various pages in the report so viewers can easily jump to the pages that are of interest to them. Recently, I've been using a stacking container with tabs that contain additional details about the report: an overview, details about data items, data cautions, and an FAQ. It's important to note that anything you can use to build a report (text, images, containers, objects) can be used to create a Table of Contents page.   As a SAS 9.4 user, do I have access to SAS Visual Analytics?  If not, what is the report generator for 9.4? SAS Visual Analytics is available in SAS 9.4. The functionality is pretty similar, although SAS Visual Analytics on SAS Viya will have additional features, and some tasks will be accomplished in a different manner. Everything discussed in the presentation (minus the Viewer Customization level, the Data-driven content object, the Report Review pane, and the SAS Viya SDK for JavaScript) will be available in SAS Visual Analytics on 9.4 and all the best practices are valid.   How would I make templates without SAS Visual Analytics? While I'm not sure how to make templates without Visual Analytics, in Visual Analytics you can make templates of pages and objects, which was briefly mentioned in the presentation. For example, once you create a page and lay out the objects as you desire, you can create a page template from that and use it in different reports. I do this a lot with my Overview or Table of Contents pages. The page template can include the objects, the options modified for those objects, and the layout of the objects. In addition, you can include data with the page templates as well. You can also create object templates that save the modified options for each object so you don't have to make the same changes repeatedly.  For more information about creating templates in Visual Analytics, see the Using Templates to Create Reports Quickly in SAS Visual Analytics or check out SAS Visual Analytics: Use Object Templates for consistency and faster report development. Outside of SAS Visual Analytics, all of these report design best practices are still valid. You will still want to draft a plan, choose the best chart (the available chart types will depend on which tool you use), focus on what's important, consider the layout, and test, test, and test again.   I'm a user of SAS Enterprise Guide. What tools would you recommend for building a report in SAS Enterprise Guide? While this presentation focused mostly on SAS Visual Analytics, it's important to remember that the report design best practices are applicable to any tool. You will want to draft a plan, choose the best chart (the available chart types will depend on which tool you use), focus on what's important, consider the layout, and test, test, and test again.   How do I access Visual Analytics with SAS 9.4? Where do I go to begin? Before you access SAS Visual Analytics at your site, you will need to contact your SAS admin. They can let you know if you have Visual Analytics licensed, will be able to direct you to the correct URL to access Visual Analytics, and will be able to assign you credentials for signing in.    Is there a link to where the layout recommendations are located? You can find report design best practices by visiting the SAS Beautiful Reports website. You can find additional resources in the attached slide deck.    Recommended Resources Please see additional resources in the attached slide deck.   Want more tips? Be sure to subscribe to the Ask the Expert board to receive follow up Q&A, slides and recordings from other SAS Ask the Expert webinars. ... View more

This is the fourth part of a six part series that describes tips and tricks for building impactful reports in SAS Visual Analytics.   Draft a Plan Choose the Best Chart  Bonus: Chart Best Practices   Focus on What’s Important (this article!) Consider the Layout Test, Test, and Test Again   SAS Visual Analytics enables you to create compelling, interactive reports that can be viewed by anyone, anywhere. To create impactful reports that resonate with your audience you need to (1) draft a plan for the report, (2) choose the best chart type to display your data, (3) create your reports so viewers can focus on what’s important to them, (4) pick a layout that will best display your data and tell your data story, and (5) test the report to ensure it operates and looks the way you want. In this post, we will focus on the third step in the process: Focus on What’s Important.   Your reports should be organized, easy to navigate, versatile, and attractive.   Organized You can organize content by adding multiple pages to your reports. Each page in your report should focus on one aspect of your data story and tell that piece with a limited number of objects (less than 6). Not only that, but you must ensure that each page can stand on its own. Viewers should not be expected to remember details from one page to understand the concepts that are communicated on another page.   In addition to adding multiple pages to your report, you can create pages that provide additional details to report viewers: hidden pages and pop-up pages. These pages can be used to communicate information about the report to other designers, describe the functionality in the report for report viewers, or they can be linked to an object on a regular page to enable viewers to see additional details.   There is no limit to the number of pages that can be added to a report or the number of objects that can be added to a page. However, it is a good idea to limit the number of pages to make your report easier to access, easier to navigate, and easier to understand.   Pro Tip! If you need more than six or seven visible pages to tell your data story, consider creating multiple reports and use links between them to provide additional information.   Easy to Navigate You can make your reports easy to navigate by adding descriptions to define the purpose of your report and instructions to describe the features of your report.   Give all objects clear, detailed titles that can help your audience understand the purpose of the object and use the Text object to add additional details and numbers when needed.   You should also include a table of contents or introductory page for the report to help explain the basics of the report. You can even use pop-up pages to provide more information about navigating the page (like detailed tips on how to use the report, descriptions of report objects, and information about actions or links). These details can be communicated via text (with the Text object) or even a video (with the Web content object)! Including detailed descriptions and instructions can help make the report more accessible and is critical for users of screen reader technology. Using text to explain actions will enable all users to better understand the structure of the report.   As a best practice, all text should use consistent fonts.   Pro Tip! When providing instructions for the report, include details about keyboard shortcuts.   Versatile You can make your reports versatile (or interactive) by adding animation, ranks, prompts, actions, links, and by setting the viewer customization level.   Animations can enable viewers to view changes in data over time. When using animations, be sure to focus on changes that are different from the norm.   Pro Tip! Be aware that the animation toolbar is not fully accessible to users of screen readers. The details table displayed when maximizing the object, however, is fully accessible. If using animation in your charts, consider including a note that instructs users to maximize the object to view a table of the same information in the animated graph.   Ranks enable viewers to focus on the most important values and can be used to identify leaders (top values) or laggers (bottom values).   Report and page prompts can help the viewer focus on areas that are important to them by enabling them to filter the report and page, respectively. Consider the placement of prompts in the report as you don’t want them to be overlooked. Use titles and text to explain the purpose of prompts and how to use them and to describe which elements are affected.   Actions can add interactivity to the report so viewers can explore data in a way that is meaningful to them. This will give them a part in the data discovery process and will increase their motivation to act on their findings.   Pro Tip! Use automatic actions to enable the viewer to tailor their experience by specifying the order in which their actions are applied. This makes the report more dynamic, increases visibility and usage of the report, and increases its value.   Links can be used to provide additional information about specific areas. You can link to another page in the report, other reports, or to an external web page. Be sure to add instructions that explain which links are available and how they work.   The viewer customization level enables you to give viewers more control over the appearance of the report by specifying a level of modification. You can set the viewer customization on the Options pane for the report. The degree of customization can be adjusted from simple edits (that will enable viewers to modify simple options for the report, such as adding labels and hiding or displaying legends) to comprehensive edits (that will enable viewers to change chart types) to data edits (that will enable viewers to modify the data used in report objects, filters, and ranks).   Attractive You can add styles and display rules to make your reports more attractive.   Pro Tip! When using display rules, it’s recommended to use a small number of display rules (2 to 3) to make your reports easier to understand and more accessible. Consider adding labels to your display rules. For expression-based display rules, the label appears in the Rules pane and in tool tips for any elements to which the display rule applies. The label is also announced by screen readers when users are viewing the report.   Be cognizant of color choices as they can affect the mood and the viewer’s reaction to a report object. These emotions may differ based on the locality or region of the world, so color choices may change depending on your audience.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   This graphic shows the positive (on the left) and negative (on the right) emotions provoked by common colors. These emotions may differ based on your locality or region.   Pro Tip! Choose WCAG (Web Content Accessibility Guidelines)- compliant colors. This will make your report more accessible for viewers who are color blind or have low vision. The W3C website provides additional information about selecting WCAG-compliant colors.   Summary After you have drafted a plan for your report and selected the best charts to display your data, you need enable your viewers to focus on what’s important. You can do this by ensuring that your reports are organized, easy to navigate, versatile, and attractive.   In the next part of this series, we discuss the layout of your report.   References Beautiful Reports   Visual Explanations by Edward Tufte   Documentation: Keyboard Shortcuts for SAS Visual Analytics   Documentation: Viewing Objects with SAS Graphics Accelerator   Documentation: Creating Accessible Reports Using SAS Visual Analytics   Documentation: Accessibility Features for SAS Visual Analytics   SAS Visual Analytics Stories Are Data With a Soul by Ted Stolarczyk     Find more articles from SAS Global Enablement and Learning here. ... View more

This is the third part of a six part series that describes tips and tricks for building impactful reports in SAS Visual Analytics.   Draft a Plan Choose the Best Chart Bonus: Chart Best Practices (this article!) Focus on What’s Important Consider the Layout Test, Test, and Test Again   SAS Visual Analytics enables you to create compelling, interactive reports that can be viewed by anyone, anywhere. To create impactful reports that resonate with your audience you need to (1) draft a plan for the report, (2) choose the best chart type to display your data, (3) create your reports so viewers can focus on what’s important to them, (4) pick a layout that will best display your data and tell your data story, and (5) test the report to ensure it operates and looks the way you want. In this post will focus on some best practices for the second step in the process: Choose the Best Chart.   To choose the best chart to display your data, there are some best practices (or general rules) you should follow.   Use the simplest graph There is no need to display something in a word cloud that can be more easily understood in a bar chart. Unusual chart types might muddle your data message and make it more difficult for people who use assistive technology (like screen readers).   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   In this example, both the bar chart and the word cloud are displaying the same information (Total Profit by Company). The profit details are easier to interpret and more easily compared in the bar chart versus the word cloud. Word clouds should be avoided if analytical accuracy is desired because it is difficult to compare the relative sizes of different words due to the number of letters in each word and the size of the letters.   Pro Tip! As you find yourself creating report objects and modifying options, you can create object templates with those options applied to speed up development time in the future. To create an object template, right-click the modified object and select Save to Objects pane. The object is added to the Objects pane with a default name (which can be modified) and available for you to use in your reports. For more information about object templates, view SAS Visual Analytics: Use Object Templates for consistency and faster report development.   Use visually appealing, easy to understand objects The type of objects you choose will depend on the audience of your report. Something that is easy to understand for statisticians might not be easy to understand for the general public.     In this example, a Cluster object (located in the Statistics group) is used in a report for statisticians, who understand the concepts of clustering and can easily interpret the various graphs. For a general audience, however, simpler objects (like key value objects and bar charts) are used and explanatory text (using the Text object) is added to explain the layout of the report and state the conclusions.   Use only the most important data Only include what is necessary to get your point across. If too much data is displayed, your viewer might miss the point of the graph.     In this example, both reports show the same information. The report on the right has additional details displayed in the key value objects (Transaction Year) and additional roles added to the bar chart (Lattice Row and Lattice Column). None of this information adds any additional context for the report and makes the report seem more cluttered and difficult to interpret than the report on the left.   Pro Tip! Lattice columns and lattice rows in charts might not be apparent to users of screen reader technology. To ensure users are aware of lattices, include a text object that describes the lattices and explains how to interact with them.   Keep graphs simple Only include what is absolutely necessary in your charts. In general, you should try to remove all chartjunk. Chartjunk refers to all visual elements in charts that are not necessary to comprehend the information presented or distract the viewer from the main point of the chart. This can include tick marks, grid lines, or unnecessary labels.     In this example, both charts show the same information. The chart on the bottom includes a lot of chartjunk: the vertical axis, gridlines, labels and tick marks for the horizontal axis, and the fill. The chart on top minimizes the amount of chartjunk making it much easier to focus on the data values.   Use a zero baseline A zero baseline is typically assumed by users and can lead to misinterpretation or tend to skew the understanding of the chart if it is not used. If you would like to compare values to some baseline other than zero (perhaps to compare the results for a drug trial to the placebo group), use a needle plot (where a zero baseline is not assumed). If you want to highlight the difference between values that are close together, use a dot plot (where a zero baseline is not assumed).     In this example, both charts show profit by area code. At first glance, the chart on the right seems to indicate that some area codes have negative profit. When taking a closer look, however, you can see this is because the baseline is set to $50,000. The chart on the left is a better representation of this data because it starts the baseline at zero, so total profit values are not misread. To compare profit for each area code to $50,000, add a reference line to the bar chart or use a needle plot instead.   Use two-dimensional charts Three-dimensional effects can distort the data and cause the viewer to miss out on vital information. Luckily, SAS Visual Analytics only produces two-dimensional charts!     In this example, both charts show revenue and costs by quarter. In the chart on the right, costs for 1st quarter 2015 and 1st quarter 2016 are hidden by the revenue values. In addition, comparing the values is very difficult and depends on the angle at which the chart is viewed. The chart on the left shows all data and makes it easier to compare the values for each quarter.   Pro Tip! For multi-line charts (like the chart on the left), it’s a best practice to rotate attributes for data element styles. This makes it easier for color blind users to read the chart by rotating the type of line drawn for the line chart (one line may be solid, the next may be dashed, and so on). To set this option, at the report-level, set the Data Element Style Rotation option to Rotate all attributes.   Choose colors wisely Use colors to promote focus in graphs, but don’t overuse colors. Less is more. Choose complementary colors that are pleasing to the eye when used side by side and can help improve readability for users who are color blind. The default palette choices in SAS Visual Analytics cycle through warm and cool colors for this purpose. In addition, ensure your colors have sufficient contrast to foreground and background elements and be aware that some colors might evoke strong emotions. These emotions may differ based on the locality or region of the world, so color choices may change depending on your audience.     In this example, the chart on the right uses too many colors (different colors are used for the title, the axes, the legend background, and the graph background). In additional, the colors used to display the left and right axes do not contrast well with the graph background, which makes the values difficult to read. The chart on the left, on the other hand, uses the default color palette in SAS Visual Analytics, so colors contrast nicely with the graph background and each other, which makes it easier for color blind users to compare values.   Pro Tip! Using SAS Theme Designer, you can create custom themes to customize the color palette used in your reports. Use the Options pane to set the theme at the report-level. For more information about creating custom themes, see Use Report Themes to quickly change your data color palette.   Keep in mind, that the data should be the focus of your report. The data helps advance your story and should be what your audience remembers about your report. As stated by the godfather of data visualization, Edward Tufte, “Above all else, show the data.”   Summary When creating a report, there are several best practices to follow regardless of chart type.   In the next part of this series, we discuss how to create your reports to focus on what’s important.   References Beautiful Reports   Envisioning Information by Edward Tufte   The Visual Display of Quantitative Information by Edward Tufte   Visual Explanations: Images and Quantities, Evidence and Narrative by Edward Tufte   SAS Visual Analytics: Use Object Templates for consistency and faster report development   Use Report Themes to quickly change your data color palette   Documentation: Keyboard Shortcuts for SAS Visual Analytics   Documentation: Viewing Objects with SAS Graphics Accelerator   Documentation: Creating Accessible Reports Using SAS Visual Analytics   Documentation: Accessibility Features for SAS Visual Analytics     Find more articles from SAS Global Enablement and Learning here. ... 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Watch this Ask the Expert session to learn how you can create reports in SAS Visual Analytics more efficiently using page and object templates.    Watch the webinar   You will learn how to: Use existing page templates to build pages more efficiently. Create custom page templates that meet the needs of your organization. Create object templates to customize and streamline your reports. The questions from the Q&A segment held at the end of the webinar are listed below and the slides from the webinar are attached.   Q&A Answered I currently use SAS 9.4. Is the Visual Analytics 8.3 compatible? And if so, how do I add it, or get setup to use it? SAS Visual Analytics 8.3 is not available on SAS 9.4. Visual Analytics 7.5 is available on SAS 9.4M6. Object templates were introduced in SAS Visual Analytics 8.3 (18w39). The ability to include data with object templates and hare object templates was introduced in SAS Visual Analytics 8.4. Page templates were introduced in Visual Analytics 8.5. Custom page templates were introduced in Visual Analytics 2020.1.3 (February 2021).   What software is this? How do I bring it up? This is using SAS Visual Analytics, available under Explore and Visualize from the applications menu in SAS Viya. Specifically, the webinar showed features available in SAS Visual Analytics 2023.10 (November 2023), although several features were available in earlier versions. Object templates were introduced in SAS Visual Analytics 8.3 (18w39). The ability to include data with object templates and hare object templates was introduced in SAS Visual Analytics 8.4. Page templates were introduced in Visual Analytics 8.5. Custom page templates were introduced in Visual Analytics 2020.1.3 (February 2021).   Can you edit object templates? You cannot edit object templates. Once you use an object template, you can make changes to it. You can modify options, you can modify data, but it doesn't change the object template itself. So, if you want to make changes to the object template for the next time you use it, you will need to make the changes and then save a new object template with those changes.   Can I share page templates I’ve created with members of my team? Yes, but you must be an application administrator. Users can create page templates, modify their own page templates, and delete them. Application administrators, on the other hand, can publish page templates. When an application administrator creates a page template, they have an extra option, Make available to all users. This will publish the custom page template to other users, who will see the published page template when they start a new session or refresh their current session. If you do have specific templates that you think everybody on your team would want to use, instead of creating them individually, you can get an application administrator to create them and then publish them. Once a page template is published, only the application administrator can modify and delete the page template.     Can I make changes to page templates after they are added to my report? Once you add the page template, you can make any changes you want. You can delete objects, reorganize content, and modify options. Be aware that those changes are not applied to the page template. If you want to make changes to the page template that are applied the next time you use it in a report, you will need to save another page template of those modifications.   Can I share object templates with my team? Yes, but you must be an application administrator. Users can create, rename, and delete their own object templates. Application administrators, on the other hand, can publish object templates. When an application administrator creates an object template, they have an extra option, Publish. This will publish the object template to other users, who will see the published object template when they start a new session or refresh their current session. If you do have specific object templates that you think everybody on your team would want to use, instead of creating them individually, you can get an application administrator to create them and then publish them. Once an object template is published, only the administrator can rename and delete the object template, but all users can hide them if they won’t be using them.     So, it is not possible to edit an object template and overwrite the previous name? Visual Analytics is a little bit different from most products. You can have multiple objects with the same name. To make your life easier, it’s a best practice to make changes to an object template, give it a new name, delete the old object template, and then rename the new one. If you use the same name, you might get the object templates confused.   How do we get details about a report? What objects are in the report, what data items (source, column name) are used in an object. Object templates, page templates, and data views are stored on the SAS Infrastructure Data Server and are stored in the SAS Content/Products/SAS Visual Analytics/Resources folder. When you export the content, a JSON file is created. Some information about the content is available in the JSON file.   There are also several codes you can use to access additional information: Ctrl + Alt + B will open the Visual Analytics diagnostics window. This window shows you the JSON (or XML) used to render the report. From this window, you can see details about the data, the visuals, the prompts and parameters, the view of the report, the actions, the display rules, and the styles. This window can also be used to save the report as a file and import it into another folder or another environment.   Ctrl + Alt + Q will open the Query Diagnostic tool. This tool can be used to investigate the issues concerning the queries that SAS Visual Analytics generates for the CAS (Cloud Analytic Services) server.  This tool can help you pinpoint which objects and queries are causing performance issues.   Ctrl + Alt + P will open the performance statistics window. This window shows the time and elapsed time needed to render the data, the report, and the application. This window can help you pinpoint which objects and queries are causing performance issues.   Ctrl + Alt + U will open the Report State window. This window shows the state for each element in the report.   In addition, you can see details about all content in SAS Viya using SAS Lineage. SAS Lineage provides a business-level impact analysis view of the assets in SAS Information Catalog. You can use SAS Lineage to view assets, their sources and outputs, and the relationships between them. For more information on SAS Lineage, see “Viewing Lineage” in the SAS Viy Platform: Data Preparation documentation. For more information on SAS Information Catalog, see the SAS Information Catalog documentation.     Recommended Resources SAS Visual Analytics: Use Object Templates for consistency and faster report development Sharing Data Views and Object Templates with other Viya environments Documentation: Using Page Templates Documentation: Using Object Templates Please see additional resources in the attached slide deck.   Want more tips? Be sure to subscribe to the Ask the Expert board to receive follow up Q&A, slides and recordings from other SAS Ask the Expert webinars. ... View more

This is the second part of a six part series that describes tips and tricks for building impactful reports in SAS Visual Analytics.   Draft a Plan Choose the Best Chart (this article!) Bonus: Chart Best Practices Focus on What’s Important Consider the Layout Test, Test, and Test Again   SAS Visual Analytics enables you to create compelling, interactive reports that can be viewed by anyone, anywhere. To create impactful reports that resonate with your audience you need to (1) draft a plan for the report, (2) choose the best chart type to display your data, (3) create your reports so viewers can focus on what’s important to them, (4) pick a layout that will best display your data and tell your data story, and (5) test the report to ensure it operates and looks the way you want. In this post, we will focus on the second step in the process: Choose the Best Chart.   When choosing the chart to best display your data and advance your data story, you need to think about the audience and the type of data you want to display (category, measure, date, datetime, time). You can ask yourself the following questions to determine the best chart:    Am I highlighting one important fact? Am I comparing two or more things? Am I showing survey or questionnaire results? Am I describing how parts relate to the whole? Am I showing the relationship between data items? Is a graph even required?   Highlighting One Important Fact   Choosing the best chart type can be determined by the type of data you want to display (category, measure, date, datetime, time) and what you are trying to showcase.   If you want to highlight one important fact, you can use a key value object or dynamic text to highlight a single number.     Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   In this example, both objects highlight a single number without any unnecessary information detracting from the value.   You can use a donut graph or a faded bar chart to draw the viewer’s attention to a specific value.     In this example, both objects use display rules to highlight important values (Internet Sale in the donut chart and Golf in the bar chart). These objects also show other values in muted colors for comparison.   Pro Tip! Use display rules to highlight important values, but take care to choose colors that are easily distinguished which can be helpful for color blind users. For more information about display rules, see the SAS Visual Analytics Display Rules: Report-Level post.   Comparing Two or More Things   For general comparisons, bar charts can be used to compare multiple pieces of data, dot plots can be used to compare groups with values that are close together, butterfly charts can be used to compare two groups across different categories, and dual axis charts can be used to compare two measures with different ranges. However, be aware that some audience members might not be familiar with dual axis charts and might misinterpret them.     In this example, the stacked bar chart uses the group role to compare quantity ordered for loyalty and non-loyalty members. For the dot plot, a zero baseline is not assumed, so it is useful for comparing values that are close together (like the number of orders by product line). The butterfly chart is useful for comparing two opposing groups (in this case, customer satisfaction for toy and novelty products). The dual axis chart makes it easy to compare two measures (like customer satisfaction and product sale) that have very different ranges. Viewing both these measures on the same axis will flatten the customer satisfaction data and make it difficult to see the relationship between the measures.   Pro Tip! Fixed axis ranges can be useful for accessibility because they enable users of sonification to understand the scale of data displayed in the object. This is especially useful when the values shown in the object can change due to filtering or drilling down in a hierarchy. However, if your data updates frequently or is likely to fall outside of the range when filtering or drilling, a fixed axis range is not recommended as values can unknowingly fall outside the fixed range.   For comparisons over time, use a line chart or a time series plot. Line charts are useful for comparing ordinal groups (like age ranges or loyalty levels), while time series plot are useful for displaying data over time (like year, month, or day). Time series plots can also be useful for spotting seasonal trends in the data.   Pro Tip! Time series plots and line charts include an option to add an overview axis. This is a scrolling axis that enables you to specify how much of the axis is displayed and what segment is displayed. While these are useful for focusing on smaller segments when there are a lot of data values, they can add clutter to the report. In addition, screen readers cannot interact with an overview axis. If an overview axis needs to be included, it’s a best practice to add another accessible object (like a list table or crosstab) that presents the same information in an accessible way. Alternatively, you can direct users to maximize the chart to view the details table.     In this example, the line chart shows quantity ordered by age group (an ordinal value) and the time series plot shows total sales by day.   Pro Tip! Animation can also be used to make comparisons over time. Be aware that the animation toolbar is not fully accessible to users of screen readers. The details table displayed when maximizing the object, however, is fully accessible. If using animation in your charts, consider including a note that instructs users to maximize the object to view a table of the same information in the animated graph.   For comparing against a benchmark, you can add reference lines or display rules to most charts.     In this example, a reference line is added to the chart on the left to compare customer satisfaction values to a target (50%) for each continent and a display rule is added to the chart on the right to highlight continents where customer satisfaction falls below 50% in pink.   Alternatively, a needle plot can be used to compare values to a baseline. A bullet gauge or a targeted bar chart can be used to compare actual values to a target.     In this example, a needle plot is used to compare profits to a set baseline ($50,000). The bullet gauge compares total sales (13M) to the goal (23M) and the targeted bar chart compares total sales for each unit to the target. For the targeted bar chart, a display rule is added to highlight the units where actual sales do not exceed target sales in pink.   Pro Tip! When working with gradients, three-color gradients (like the one used for the bullet gauge) are not accessible for color deficient users. Instead use two-color gradients and choose starting and ending colors with sufficient contrast or difference in luminosity.   Showing Survey or Questionnaire Results   If you want to display the results of a survey or questionnaire, you can use a stacked bar chart to compare Likert responses, a vertical bar chart (or column bar chart) for all that apply questions, or a table or crosstab if precision is important. A Likert is a global scale that is used to assess opinions, attitudes, and views; a 5-point example of a Likert scale would be the following choices: strongly agree, agree, neither agree nor disagree, disagree, and strongly disagree. Box plots can also be used to show the average response, the minimum and maximum values, and outliers. Many people might be unfamiliar with box plots, so it might be helpful to provide an explanation or display the same information in an alternative way.     In this example, the stacked bar chart displays the response percentage for a Likert scale (choose one), the vertical bar chart shows the number of responses for a question where users can select all that apply, and the crosstab shows the average response. The box plot displays the average response (diamond), the median response (line), and the minimum and maximum responses (the whiskers).   Describing How Parts Relate to the Whole   When describing how parts relate to the whole, a donut chart or pie chart can be useful for comparing less than 5 data points and treemaps can display many more data points and two measures (one to size the tile and one to color the tile).     In this example, the donut chart and pie chart show the percent quantity ordered for each age group (5 distinct values) and the treemap shows the number of orders and customer satisfaction by product make.   Pro Tip! Use pie charts sparingly. It is very difficult to compare the relative sizes of slices in the pie chart. To make the comparison easier, add data labels to each slice.   In addition, stacked bar charts can be normalized to show percent of total, histograms can be used to show ranges and intervals, and geo maps can be used when location is an important part of the analysis. Consider supplementing geo maps (which may be difficult to interpret) with more easily understood objects (like tables or crosstabs).     In this example, the bar chart options are modified to set the Grouping style to Stacked (so one bar is displayed for each continent) and the Group scale to Normalize groups to 100% (so the bar shows the relative contribution for each order type). The histogram shows the range of values for vendor satisfaction, which can be useful for modeling, and shows the number of values that fall within each range.     In this example, the geo map shows customer locations on a map background which makes it easier to see areas with a high concentration of customers.   Showing the Relationship Between Data Items   To show the relationship between two measures, use a scatter plot or heat map. Scatter plots are great for low cardinality measures or small data sources and heat maps are better at displaying high cardinality measures or large data sources.     In this example, the scatter plot displays the relationship between two measures (total profit and annual salary) and uses color to show differences between job titles. The heat map displays the relationship between two measures (product sale and customer satisfaction) and uses color to show the number of observations within each range.   Use a bubble plot to show the relationship between three measures or a correlation matrix to show the linear relationship between many measures.     In this example, the bubble plot shows the relationship between three measures and uses color to show differences between age groups: two measures (profit and days to delivery) determine bubble placement and one measure (quantity ordered) determines bubble size. The correlation matrix shows the linear relationship between many measures and uses color to shows the strength of the relationship (where lighter cells indicate a weak relationship or correlation value near 0 and darker cells indicate a strong relationship or correlation values near 1 or -1).   Pro Tip! It’s a best practice to limit the number of digits displayed after decimal points in your charts unless they are required for precision.   In addition, you can use a network diagram to show many relationships (like relationships between users of social media or parties of interest in a terrorist network), a path analysis object to show process flows (like steps in a process), or a text object to add a detailed description when no visual is possible.     In this example, the network diagram shows the relationship between employees in an organization and uses color to indicate the department of each employee. The text object shows a bulleted list of steps to complete when moving, which don’t need to be completed in a specific order.     In this example, the path analysis object shows the steps in the drug approval process, which do need to be completed in a specific order and uses color to show where drugs dropped off or did not move on to the next phase.   Pro Tip! It’s especially important to ensure that legends are displayed on all screen sizes. If legends are not displayed in the chart, they can only be viewed when the user activates a collapsed button. This button does not have an accessible name or role, so it’s not useful for users of screen reader technology.   Is a Graph Even Required?   In some cases, a graph might not need to be used to display your data. Word clouds, images, or illustrations created with the Data-driven content object might better communicate your point. In addition, a Text object can be used to give context to certain data values or state the conclusions that can be inferred from the data.     In this example, the word cloud is used to show the top recipe searches on a website. Recall that word clouds should be avoided if analytical accuracy is desired because it is difficult to compare the relative sizes of different words due to the number of letters in each word and the size of the letters.   In this example, the Image object is used to show the components of a model car and to display an illustration, and the text object summarizes the data presented in other objects and draws conclusions based on those values.   Pro Tip! When using text to provide instructions, avoid using sensory characteristics (like the size of the object, the shape of an item, or the position of the object on the screen) as the sole means of conveying information or identifying a portion of the report. This makes the report more accessible for users of screen reader technology.   Summary   After you have drafted a plan for your report, you need to choose the best chart for displaying your data. Choosing an appropriate chart is more of an art than a science, but several rules are available to aid you in showcasing your data and recommendations are made for charts that most closely aligns with the data you want to present and the details you want to showcase. There is no correct choice when choosing a chart type, but there are many incorrect choices. If you don’t believe me, listen to two experts on data visualization:   “… the only thing worse than a pie chart is several of them.” – Edward Tufte   “Save the pies for dessert.” – Stephen Few   If you want to apply the skills learned in this post to a report created in SAS Visual Analytics, take the report design challenge.   In the next part of this series, we discuss some chart best practices.   References   Beautiful Reports   Envisioning Information by Edward Tufte   The Visual Display of Quantitative Information by Edward Tufte   Visual Explanations by Edward Tufte   Documentation: Keyboard Shortcuts for SAS Visual Analytics   Documentation: Viewing Objects with SAS Graphics Accelerator   Documentation: Creating Accessible Reports Using SAS Visual Analytics   Documentation: Accessibility Features for SAS Visual Analytics       Find more articles from SAS Global Enablement and Learning here. ... View more

This is the first part of a six part series that describes tips and tricks for building impactful reports in SAS Visual Analytics.   Draft a Plan (this article!) Choose the Best Chart Bonus: Chart Best Practices Focus on What’s Important Consider the Layout Test, Test, and Test Again   SAS Visual Analytics enables you to create compelling, interactive reports that can be viewed by anyone, anywhere. To create impactful reports that resonate with your audience you need to (1) draft a plan for the report, (2) choose the best chart type to display your data, (3) create your reports so viewers can focus on what’s important to them, (4) pick a layout that will best display your data and tell your data story, and (5) test the report to ensure it operates and looks the way you want. In this blog, we will focus on the first step in the process: Draft a Plan.   Draft a Plan   When drafting a plan, you need to select the data you want to use for the report, think about your audience, craft your data story, and sketch the design of the report.   Select your Data   Before you start creating your report in SAS Visual Analytics, you need to select your data. This data can be stored in any format (SAS datasets, Microsoft Excel files, database tables, or text files) and can even exist in multiple tables. You can combine the tables before using them in SAS Visual Analytics or you can create data joins and aggregated tables within your report. You can even use multiple data sources.   Pro Tip! As a best practice, you should prepare your data before using it in SAS Visual Analytics. Data joins and aggregated tables created in Visual Analytics use temporary CAS tables that are created for each user who views the report. This can impact the performance of your report. In addition, using SAS code to prepare your data will provide you with more advanced functionality (like functions that can improve data quality, multi-table joins, non-equijoins, and more).   You can also create a variety of data items in SAS Visual Analytics using one-click calculations (like the difference from the previous period or the distinct count), hierarchies (which enable you to view different levels of your data and create a drill-down functionality for your charts), geography data items (that can be used for mapping), parameters (which give report viewers more control over the report), and statistical data items (like interaction effects, spline effects, and partitions).   Know your Audience   Next, you need to determine the audience of the report. The needs and interests of your audience will determine what you present, how you present it, and the level of detail you’ll include in the report.   For example, if you are creating a report for statisticians, you might use models (like the Statistics and Machine Learning objects) and advanced analytic objects (like automated explanation, automated prediction, forecasting, network analysis, path analysis, and text topics). For this audience, these models will be self-explanatory, and you might not have to include a lot of detail about how the model works, the purpose of the model, and why it’s useful for the report. On the other hand, if you are building a report for a general audience (like the public or your non-statistician customers), you might want to use simpler graphs that are easier to interpret and understand. In addition, you might include additional instructions and explanatory text in the report to explain the purpose and usefulness of objects and the report itself.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   In this example, a Cluster object (located in the Statistics group) is used in a report for statisticians, who understand the concepts of clustering and can easily interpret the various components. For a general audience, however, simpler objects (like key value objects and bar charts) are used instead, and explanatory text (using the Text object) is added to explain the layout of the report and state the conclusions.   Pro Tip! Regardless of your audience, it’s a best practice to provide instructions for using the report (including tips on navigating the interface, if necessary) and to give context to your graph content. This will enable your viewers to identify the key takeaways of the report and can incite them to act on those findings.   Your audience will also give you a good idea about the level of modifications you want to allow for the report. You can control the level of modification for each report by setting the Customization level for the report. The degree of customization can be adjusted from simple edits (that will enable viewers to modify simple options for the report, such as adding labels and hiding or displaying legends) to comprehensive edits (that will enable viewers to change chart types), to data edits (that will enable viewers to modify the data used in report objects, filters, and ranks).       This example shows the options available for a bar chart when the Viewer customization level is set to simple edits, comprehensive edits, and data edits.   Craft your Story   Your reports should focus on telling a single data story. When you begin to craft your story, consider these questions:   Are you trying to persuade your audience? Are you presenting facts? Do you want the audience to act?   The answers to these questions will help you determine how to present your findings in the report and will help you start constructing your narrative. Storytelling helps your audience feel more connected to your report by eliciting emotion and triggering memory. Telling a good story that resonates with your audience will make it more likely that they will remember what the report has to say and will want to act on those findings.   Sketch Design   Finally, you should roughly sketch out the design of the report. This can be anything from a bulleted outline of the report, a rough table of contents, or a hand drawn draft of each page that shows the anticipated layout, the types of objects that will be used on each page, and an explanation of how each page contributes to the overall data story. You should always keep the story in mind when building the report, from the very first sketch to the fully completed, and tested report.   Also in this stage, you should start planning for accessibility. Think about the audience and what functionality they may need to better interact with your report. For example, you can plan to add a table representation for each graph to more easily enable viewers to see specific values, you can add simpler graphs as an alternative to more complex graphs, or you can add additional information about keyboard shortcuts in SAS Visual Analytics or more details for users of screen-reader technology.   Summary   Before you begin to create your reports in SAS Visual Analytics, you need to draft a plan. In this initial step, you need to select the data you want to use for the report, think about your audience, craft your data story, and sketch the design of the report.   In the next part of this series, we discuss best practices for choosing the best chart for displaying your data.     References   Documentation: Managing Data Documentation: Keyboard Shortcuts for SAS Visual Analytics Documentation: Viewing Objects with SAS Graphics Accelerator Documentation: Creating Accessible Reports Using SAS Visual Analytics Documentation: Accessibility Features for SAS Visual Analytics Telling Your Data Story by Atrin Assa SAS Visual Analytics Stories are Data With a Soul by Ted Stolarczyk     ... View more

This is the fourth part of a four part series that discusses how to display product photos in SAS Visual Analytics.   Basics Validating Data Debugging Viewing Multiple Photos (this article!)   Scenario   In previous posts, we created a visualization to display an image of a selected product in a Visual Analytics report or the company logo if no product was selected. In this post, we will see how to display multiple photos if more than one product (or no product) is selected in the report. To do this, we will need to restructure the data passed from Visual Analytics (in JSON format) to an array of objects so it can be more easily used in the JavaScript code and then update the code to display an image gallery instead of a single image.   Note: More detail about the requirements and steps for using the data-driven content object in Visual Analytics can be found in the first post in this series.   Note: The entire code is available at the end of this post.   Updating Sample Data   First, we need to update the sample data message to contain multiple rows instead of a single row.      Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   Notice that the rowCount, availableRowCout, and data values are updated to show multiple rows. For more information about how data is passed from Visual Analytics to the third-party visualization, see the third post in this series.   Restructuring the Data   Now that we are using more than one row of data in our JavaScript code, we need to restructure the data from a two-dimensional array to an array of objects. This is done if the data passed from Visual Analytics is valid (which is determined by referencing the validateRoles function in the contentUtil.js utility).     Now, the data values can be referenced using data[i].item, where data[0].item references the first data value (the value Figure from the sample data), data[1].item references the second data value (the value Game from the sample data), and so on.   Gallery of Images   Finally, the JavaScript code needs to be updated to display one image (at full width) if one product line is selected, and a gallery of images (two per row) if more than one product line is selected.     For this example, a div (with a class of row) is created to hold all images (rowDiv) and appended to the web page inside the div (with an id of photo).   Then, a new div is created for each image using the for loop (colDiv).   If one row is passed, the div (and the image) spans the entire width (using the Bootstrap class of col-12). If more than one row is passed, the div (and each image) spaces half the width (using Bootstrap class of col-6).   Then, a Bootstrap class of py-2 is added to insert padding on the top and bottom of each image and colDiv is added to the DOM (using the appendChild method).   Lastly, a new img element is created for each row of data passed from Visual Analytics (using the createElement property), attributes of the element are modified (src and alt), and the element is added to the DOM (using the appendChild method).   The src attribute points to the image for the selected product line in the images folder. Note that the toLowerCase method is needed convert the product line passed from Visual Analytics (which is proper case) to the case used for the image file (which is in lower case). The alt attribute is the value of the selected product line. A Bootstrap class (img-fluid) is also added to the image to ensure the image takes up 100% of the width of the div (colDiv).   Testing   When the code is complete, you can test it in Visual Analytics. Notice that page prompts have been relocated to the left of the canvas and the page prompt has been changed to a list control (so users can select multiple product lines). In addition, a data-driven content object (that references the code) is included on the canvas.     Notice when no product line is selected, images for all product lines are displayed in the data-driven content object.   Pro Tip: Recall that to use list controls in the page prompt or report prompt areas, the location of the prompts need to be on the left or the right or a prompt container needs to be used. In this example, I changed the location of the page prompt container to the left side.   When one product line is selected, an image for that product line is displayed and it takes up the full width of the object.     When more than one product line is selected, images for those product lines are displayed and take up half the width of the object and subsequent images are added below the others.     Summary   You can use similar code to restructure data passed from Visual Analytics from a two-dimensional array to an array of objects and to display multiple images in your report.   References   Documentation: Working with Data-Driven Content   Programming Considerations for Data-Driven Visualizations   SAS GitHub repository for third-party visualizations    Book: Interactive Reports in SAS Visual Analytics      Find more articles from SAS Global Enablement and Learning here.   Code   Below is the code in its entirety.   <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Document</title> <!-- Bootstrap --> <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.0.2/dist/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-EVSTQN3/azprG1Anm3QDgpJLIm9Nao0Yz1ztcQTwFspd3yD65VohhpuuCOmLASjC" crossorigin="anonymous"> <!-- Utilities for DDC --> <script type="text/javascript" src="util/messagingUtil.js"></script> <script type="text/javascript" src="util/contentUtil.js"></script> </head> <body> <!-- Container for Photos --> <div class="container" id="photo"> <!-- <div class="row"> <div class="col py-2"> <img src="images/figure.jpg" alt="Figure" class="img-fluid"> </div> <div class="col py-2"> <img src="images/game.jpg" alt="Game" class="img-fluid"> </div> <div class="col py-2"> <img src="images/plush.jpg" alt="Plush" class="img-fluid"> </div> <div class="col py-2"> <img src="images/bead.jpg" alt="Bead" class="img-fluid"> </div> </div> --> </div> <!-- Custom JavaScript --> <script> // Listening for HTML document completely loaded and parsed, best practice document.addEventListener("DOMContentLoaded", function() { /******************************* Declare variables ***************************************/ // Sample data message to render outside of VA for debugging const sampleData = { "version": "1", "resultName": "dd55", "rowCount": 5, "availableRowCount": 5, "data": [ [ "Figure" ], [ "Game" ], [ "Plush" ], [ "Beach" ], [ "Bead" ] ], "columns": [ { "name": "bi79", "label": "Product Line", "type": "string" } ] }; // Dynamic data variables let vaMessage; // Data message from VA let vaResult; // Name of DDC object, required to send messages back to VA let rowCount; // Number of rows passed from VA let data; // Data to be parsed from VA data message // Selection variables let photoDiv; // Div for photo let rowDiv; // Div for row let colDiv; // Div for col let itemPhoto; // Element for photo /******************************* Setup Callback Functions ***************************************/ // Attach event for data message from VA va.messagingUtil.setOnDataReceivedCallback(onDataReceived); // If not being rendered in iFrame (outside of VA), render with sample data if (!inIframe()) { onDataReceived(sampleData); } // Take action on received data function onDataReceived(messageFromVA) { // Initialize data variables vaMessage = messageFromVA; vaResult = messageFromVA.resultName; rowCount = messageFromVA.rowCount; // Validate data roles if ( !va.contentUtil.validateRoles( messageFromVA, ["string"], // data from DDC object ["number"] // additional field for brush column (not needed in this example) ) ) { // If roles are invalid or no data is being passed, display a message in VA about required roles (requires https) va.messagingUtil.postInstructionalMessage( vaResult, "Display Photo expects columns to be assigned in this order:\n" + " 1. Item (string)" ); } else { // Restructure data from 2d array to array of objects data = []; for (let i = 0; i < vaMessage.data.length; i++) { data.push({ item: vaMessage.data[i][0], index: i }); } } // Add photo to DOM const photoDiv = document.getElementById("photo"); photoDiv.innerText = ""; const rowDiv = document.createElement("div"); rowDiv.classList.add("row"); photoDiv.appendChild(rowDiv); for (let i = 0; i < data.length; i++) { const colDiv = document.createElement("div"); if (rowCount == 1) { colDiv.classList.add("col-12"); } else { colDiv.classList.add("col-6"); } colDiv.classList.add("py-2"); rowDiv.appendChild(colDiv); itemPhoto = document.createElement("img"); itemPhoto.src="images/"+data[i].item.toLowerCase()+".jpg"; itemPhoto.alt = data[i].item; itemPhoto.classList.add("img-fluid"); colDiv.appendChild(itemPhoto); } }; /******************************** Helper functions *****************************************/ function inIframe() { try { return window.self !== window.top; } catch (e) { return true; } }; }); </script> </body> </html>       ... 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