{"id":6891,"date":"2014-03-07T14:38:15","date_gmt":"2014-03-07T09:08:15","guid":{"rendered":"http:\/\/blog.fusioncharts.com\/?p=6891"},"modified":"2026-01-20T14:41:19","modified_gmt":"2026-01-20T09:11:19","slug":"to-explain-or-explore-that-is-the-question-in-data-visualization-podv","status":"publish","type":"post","link":"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/","title":{"rendered":"Explain vs Explore: Decoding Data Visualization Goals 2026"},"content":{"rendered":"<p><em>This is the second post in our series <a href=\"https:\/\/www.fusioncharts.com\/blog\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u2018Principles of Data Visualization\u2019 #PoDV<\/a><\/em><\/p>\n<p>Whether you create visualizations for product dashboards or interact with them in your daily work, understanding the underlying goal is one way to get the most out of visualizations. It creates the right expectations before you begin creating or analyzing the visual, resulting in better results.<\/p>\n<p>In this post, we&#8217;ll look at two common data visualization goals and how they apply to real-world examples. \u00a0If you\u2019re looking for a\u00a0<a href=\"https:\/\/www.fusioncharts.com\/fusioncharts\">Data Visualization Tool<\/a>, we suggest using fusioncharts for data visualization.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_71 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\"><p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<\/div><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#Two_Goals_in_Data_Visualization\" title=\"Two Goals in Data Visualization\">Two Goals in Data Visualization<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#1_Explain_the_Data_to_Tell_a_Story\" title=\"1. Explain the Data to Tell a Story\">1. Explain the Data to Tell a Story<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#2_Explore_Large_Data_Sets_to_Discover_Many_Stories\" title=\"2. Explore Large Data Sets to Discover Many Stories\">2. Explore Large Data Sets to Discover Many Stories<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#The_Hybrid_Model\" title=\"The Hybrid Model\">The Hybrid Model<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#Examples_From_Daily_Life\" title=\"Examples From Daily Life\">Examples From Daily Life<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#A_Speedometer\" title=\"A Speedometer\">A Speedometer<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#The_London_Underground_Map\" title=\"The London Underground Map\">The London Underground Map<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#Blog_Tag_Cloud\" title=\"Blog Tag Cloud\">Blog Tag Cloud<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#Google_Maps\" title=\"Google Maps\">Google Maps<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#Google_Hot_Trends_Fullscreen\" title=\"Google Hot Trends Fullscreen\">Google Hot Trends Fullscreen<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/#Explain_or_Explore_The_Choice_is_Yours\" title=\"Explain or Explore? The Choice is Yours\">Explain or Explore? The Choice is Yours<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Two_Goals_in_Data_Visualization\"><\/span>Two Goals in Data Visualization<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p dir=\"ltr\">In a business context, the two main goals that visualizations have are to:<\/p>\n<ul>\n<li>Explain<\/li>\n<li>Explore<\/li>\n<\/ul>\n<p>Let\u2019s discuss each of these goals in detail.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"1_Explain_the_Data_to_Tell_a_Story\"><\/span>1. Explain the Data to Tell a Story<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p dir=\"ltr\">As mentioned in the <a href=\"https:\/\/fusioncharts.com\/blog\/everyone-does-it-but-no-one-talks-about-it-data-visualization-podv\/\" target=\"_blank\" rel=\"noopener noreferrer\">first post<\/a>, the reason we visualize data is to tell a story. If the designer of the visual has a story to tell the viewer with the data, the goal of the visual is to explain. There is a defined structure starting from the main narrative, and trickling down to each part of the visual. These visuals are effective for making a point or conveying an insight from the data. For example, the main narrative in the simple column chart below is to highlight the country with the highest value:<\/p>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6903\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/1.-column-chart.png\" alt=\"Column Chart\" width=\"351\" height=\"234\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/1.-column-chart.png 922w, \/blog\/wp-content\/uploads\/2014\/03\/1.-column-chart-150x100.png 150w\" sizes=\"auto, (max-width: 351px) 100vw, 351px\" \/><\/h2>\n<p><!--more--><\/p>\n<p dir=\"ltr\">The designer of this visual starts by asking a question of the data &#8211; Which is the highest value? &#8211; and designs the chart to simply answer this question. The viewer follows a similar process when interpreting the chart. This process can be understood by the following illustration:<\/p>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6906\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/4.-explanatory-data-visualization.png\" alt=\"Explanatory Data Visualization\" width=\"482\" height=\"119\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/4.-explanatory-data-visualization.png 599w, \/blog\/wp-content\/uploads\/2014\/03\/4.-explanatory-data-visualization-150x37.png 150w\" sizes=\"auto, (max-width: 482px) 100vw, 482px\" \/><\/h2>\n<p>Explanatory visuals are editorially driven, that is, the designer leaves little to the imagination of the viewer, and crafts the visual with care to bring out the story most clearly. Presentation and design become important. All effort is made to reduce noise from the visual, so there are no distractions from the main narrative. Due to this, most explanatory visuals tend to be static and not interactive. This gives more creative control to the designer and makes it easier to direct the process of interpretation.<\/p>\n<p>This type of visualization is used in business scenarios for the following tasks:<\/p>\n<ul>\n<li>\u00a0 Answer a question. E.g., How much sales did we have last quarter?<\/li>\n<li>\u00a0 Support a decision. E.g., We need to stock more football jerseys as they were sold out on most days last week<\/li>\n<li>\u00a0 Communicate information. E.g., Revenue is on track for this quarter<\/li>\n<li>\u00a0 Increase efficiency. E.g., &#8220;Technical specifications&#8221; is the most viewed section on the product page. It should be given more visibility.<\/li>\n<\/ul>\n<p>Most of the visualizations we come across in daily scenarios fall in this category. In business, they appear in product dashboards, business presentations, training materials, and marketing content. They\u2019re also used in the media for advertising, print and television journalism, and political campaigning.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"2_Explore_Large_Data_Sets_to_Discover_Many_Stories\"><\/span>2. Explore Large Data Sets to Discover Many Stories<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p dir=\"ltr\">Explanatory visuals are not editorially driven, but rather are viewer-driven. The emphasis is not on a single important story but on discovering many small stories in the visual. The designer may not even be sure what story is there in the data. The aim of the designer is to present the data in a way that invites the viewer to notice the obvious and discover surprising insights. It simply gives away a number of ideas for the viewer to make something meaningful. For example, below is a visualization of the State of the Union address of recent Presidents:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6905\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/3.-presidents-state-of-the-union.png\" alt=\"heatmap of presidents state of the union\" width=\"560\" height=\"215\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/3.-presidents-state-of-the-union.png 625w, \/blog\/wp-content\/uploads\/2014\/03\/3.-presidents-state-of-the-union-150x58.png 150w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/><\/p>\n<p>Here, the viewer starts by becoming familiar with the visual, then identifies an area of interest. For example, \u2018Which President spoke most about jobs?\u2019 She then explores the \u2018Jobs\u2019 section of the visualization and finds her answer &#8211; Barack Obama. She could then move on to exploring other areas of the visualization.<\/p>\n<p dir=\"ltr\">Exploratory visuals invite the viewer to get an overview of the visual, ask questions along the way, and find answers to those questions. The process can be illustrated as follows:<\/p>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6904\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/2.-exploratory-data-visualization.png\" alt=\"Exploratory Data Visualization\" width=\"464\" height=\"109\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/2.-exploratory-data-visualization.png 599w, \/blog\/wp-content\/uploads\/2014\/03\/2.-exploratory-data-visualization-150x35.png 150w\" sizes=\"auto, (max-width: 464px) 100vw, 464px\" \/><\/h2>\n<p>This process can be cyclical without a specific endpoint. It doesn\u2019t follow a particular order, and the viewer can find many insights or none at all. The outcome can be to gain awareness of a topic rather than to make a specific decision. This type of visualization can accomplish the following tasks:<\/p>\n<ul>\n<li>\u00a0 Pose new questions<\/li>\n<li>\u00a0 Discover new areas of interest<\/li>\n<\/ul>\n<p>Exploratory visuals work well when there\u2019s a high volume of data to visualize. The designer tolerates some level of noise in the visual to give the viewer more granularity. Because of the granularity of the data, exploratory visuals are often interactive rather than static. For example, the visual could use a drill-down feature to show or hide the various paths available to the viewer. In this case, the visual functions as an interface to the data.<\/p>\n<p>Though they&#8217;re not as popular, exploratory visualizations have been gaining prominence in recent years with the rise of big data. The high volume of data and varied data sets that have become common today can only be analyzed using exploratory visuals.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Hybrid_Model\"><\/span>The Hybrid Model<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p dir=\"ltr\">When viewing a visual, the easiest way to tell the type of visualization is to ask who does the work to reveal insights from the data. If the designer has done the work and made the insights clear, it\u2019s an explanatory visual. If the viewer needs to find insights that the designer hasn\u2019t made clear, it\u2019s an exploratory visual. That said, most visualizations fall somewhere in-between. Most visualizations are based on a curated data set that allows some, or a lot of exploration. When designing a visualization it\u2019s important to balance both elements &#8211; explanation, and exploration.<\/p>\n<p>Now that we have a good understanding of the two goals of visualizations, let\u2019s look at a few common examples that we come across in our daily lives.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Examples_From_Daily_Life\"><\/span>Examples From Daily Life<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"A_Speedometer\"><\/span>A Speedometer<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6907\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/5.-speedometer.jpg\" alt=\"speedometer\" width=\"245\" height=\"188\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/5.-speedometer.jpg 600w, \/blog\/wp-content\/uploads\/2014\/03\/5.-speedometer-150x116.jpg 150w\" sizes=\"auto, (max-width: 245px) 100vw, 245px\" \/><\/p>\n<p dir=\"ltr\">This visual is designed to convey just one metric &#8211; speed. There is no exploration to be done here. It\u2019s a great example of an explanatory visual.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"The_London_Underground_Map\"><\/span>The London Underground Map<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p dir=\"ltr\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6908\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/6.-london-underground-map.gif\" alt=\"london underground map\" width=\"472\" height=\"379\" \/><\/p>\n<p dir=\"ltr\">The London metro map though packed with information is explanatory. It\u2019s designed to show the best route from point A to B, and the designer has done the work to make it do just that. The viewer comes with the question \u2018How do I get from point A to B?\u2019, looks at the map, and finds the route.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Blog_Tag_Cloud\"><\/span>Blog Tag Cloud<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p dir=\"ltr\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6909\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/7.-tagcloud-example.png\" alt=\"tagcloud-example\" width=\"327\" height=\"250\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/7.-tagcloud-example.png 715w, \/blog\/wp-content\/uploads\/2014\/03\/7.-tagcloud-example-150x115.png 150w\" sizes=\"auto, (max-width: 327px) 100vw, 327px\" \/><\/p>\n<p dir=\"ltr\">We\u2019ve all seen tag clouds on blogs. They highlight the most-used tags from the blog, and in that sense are explanatory, giving emphasis to the bigger words. However, they also show many less frequent tags that invite exploration. They\u2019re a great example of a hybrid visualization.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Google_Maps\"><\/span>Google Maps<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p dir=\"ltr\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6910\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/8.-google-maps-example.png\" alt=\"google maps example\" width=\"329\" height=\"250\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/8.-google-maps-example.png 487w, \/blog\/wp-content\/uploads\/2014\/03\/8.-google-maps-example-150x114.png 150w\" sizes=\"auto, (max-width: 329px) 100vw, 329px\" \/><\/p>\n<p dir=\"ltr\">Google Maps is also a hybrid visualization. It can be used to explain the driving directions from point A to B, similar to the London Underground map &#8211; explanatory. It also allows zooming and panning to discover the surrounding areas, and landmarks &#8211; exploratory.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Google_Hot_Trends_Fullscreen\"><\/span>Google Hot Trends Fullscreen<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p dir=\"ltr\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-6911\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/9.-google-hot-trends-example.png\" alt=\"google-hot-trends-example\" width=\"599\" height=\"317\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/9.-google-hot-trends-example.png 770w, \/blog\/wp-content\/uploads\/2014\/03\/9.-google-hot-trends-example-150x79.png 150w\" sizes=\"auto, (max-width: 599px) 100vw, 599px\" \/><\/p>\n<p dir=\"ltr\">If you\u2019ve not come across this visualization, <a href=\"https:\/\/www.google.com\/trends\/hottrends\/visualize?nrow=5&amp;ncol=5&amp;pn=p1\" target=\"_blank\" rel=\"noopener noreferrer\">do take a look<\/a>. It\u2019s quite fascinating. It visualizes Google search queries in real-time in the form of a colorful grid. The queries keep changing every second. This visualization doesn\u2019t highlight any single search query but rather invites the viewer to explore any part of the visual to find out what users are searching for right now. The story is left to the viewer to discover. This sort of visualization is possible only with the scale of big data. It\u2019s a great example of an exploratory visualization.<\/p>\n<h2 dir=\"ltr\"><span class=\"ez-toc-section\" id=\"Explain_or_Explore_The_Choice_is_Yours\"><\/span>Explain or Explore? The Choice is Yours<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p dir=\"ltr\">In summary, the two main goals of visualizations are to explain or to explore data. Most visuals are a hybrid of both goals. When designing a visual it pays to decide at the outset what balance the visual should have &#8211; more explanatory, or more exploratory. This single technique can greatly improve the quality of visualizations, and result in even better storytelling.<\/p>\n<p>This post is the second in a series of posts. If you\u2019d like to get the lowdown on what\u2019s in this series from start to end, read our white paper \u2018<a href=\"https:\/\/www.fusioncharts.com\/whitepapers\/downloads\/Principles-of-Data-Visualization.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">Principles of Data Visualization<\/a>.\u2019 You don\u2019t even have to fill in a download form to read it.<\/p>\n<p>In the next post, we\u2019ll dive into the mechanics of how we process visual information. We&#8217;ll consider the role of memory in perceiving visual information, and how to apply that understanding as we work with visualizations. Stay tuned!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This is the second post in our series \u2018Principles of Data Visualization\u2019 #PoDV Whether you create visualizations for product dashboards or interact with them in your daily work, understanding the underlying goal is one way to get the most out of visualizations. It creates the right expectations before you begin creating or analyzing the visual, [&hellip;]<\/p>\n","protected":false},"author":12,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[105,463],"coauthors":[696],"class_list":["post-6891","post","type-post","status-publish","format-standard","hentry","category-thoughts","tag-data-visualization","tag-principles-of-data-visualization"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Explain vs Explore: Decoding Data Visualization Goals 2026<\/title>\n<meta name=\"description\" content=\"Master the principles of data visualization in 2026. Part 2 of our series covers essential tips for creating impactful product dashboards. Follow guide.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.fusioncharts.com\/blog\/to-explain-or-explore-that-is-the-question-in-data-visualization-podv\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Explain vs Explore: Decoding Data Visualization Goals 2026\" \/>\n<meta property=\"og:description\" content=\"Master the principles of data visualization in 2026. Part 2 of our series covers essential tips for creating impactful product dashboards. 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