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As analytics grows, data visualization supports business forecasting, trends, and growth via diagrams and dashboards across paper, screens, or projectors. This study compares two open tools, Data-Driven Documents (D3.JS) and Google Charts, using a retail customer-data scenario with 30 recruited participants.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/towards-effective-customer-data-visualization-data-driven-documents-d3js-vs-google-charts/657592/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/towards-effective-customer-data-visualization-data-driven-documents-d3js-vs-google-charts/657592.png","ImageObject",300,407,{"name":92,"@type":93},"LangkahRina","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-10-26",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does the study address about data analytics outputs?","Question",{"text":112,"@type":113},"Most analysis results are presented as raw numbers that are hard for customers to interpret. 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The study also highlights that tool presentation and ease of use can affect users’ effectiveness, efficiency, and preference.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},657592,1793136390,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":36},962090893776,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","TOWARDS EFFECTIVE CUSTOMER DATA VISUALIZATION: DATA-DRIVEN DOCUMENTS (D3.JS) VS. GOOGLE CHARTS  \nCindi Smatt, University of North Georgia  \nRenée Pratt, University of North Georgia  \nTamirat Abegaz, University of North Georgia  \nAllie Dobbs, University of North Georgia  \nABSTRACT  \nOrganizations today are in vital need of viewing, interacting, and interpreting vast amounts of data in quick easy design views. Management wants to visualize business growth, forecasting and trends in diagrams and dashboards. With an increase in data analytics, data visualization is a way to display information in a visual manner whether on paper, a computer screen, or a projector. Data-Driven Documents have become increasingly more important in the corporate world. It is becoming a new and popular way to share data in an interactive and creative way. With numerous tools designed to facilitate these data visualization needs, it becomes difficult to know and understand what users interpret as easy, useful, and/or efficient. We explore two popular freely available data visualization tools: D3.JS and Google Charts Tools for retail customer data. Thirty participants were recruited for the study. However, only 29 participants completed the task. A paired sample t-test was performed. The results indicated that D3.JS is more efficient than Google Charts, however Google Charts is more user friendly than D3.JS. Our research highlights the significance that different visualization tools may amplify users’levels of effectiveness, efficiency and preference based on its presentation and ease of use. Therefore, organizations should be mindful to their selection of data visualization tools and their audience.  \nKeywords: Data Visualization, Data-Driven Documents, Google Charts, D3.JS, Open Source  \nINTRODUCTION  \nBusinesses collect and access more data today than they ever imagined. The challenge with large datasets is interpreting and presenting data in an easy and understandable form (Qin, Luo, Tang, & Li, 2020; Wang, Yang, Wang, Sherratt, & Zhang, 2020) . Data analysis and presentation has proven to be an important aspect to every business (Jin, Wah, Cheng, & Wang, 2015), and thus creates a larger demand for better data analytic tools. One challenge that businesses have is that the results of most analyses are simply raw numbers and very difficult for the customer to interpret as is. Therefore, there is a demand for easier to read, interactive data results (Center, 2013), also known as data visualization. Data (or information) visualization is the representation or presentation of data/information in a visual and meaningful graphical form such as charts, diagrams, maps, plots, etc. Data visualization enables end-users to analyze more effectively and efficiently the relationships among the represented data.  \nGraphical interpretations become increasingly essential with the excessive amount of data available (Fu et al., 2014) . Visual diagrams are useful at gaining the customer’s attention because visuals are more likely to reach the customer, as it does not require an understanding of a language code but goes beyond specific experiences (Hariharan & Krithivasan, 2016) . In addition to obtaining their attention, the diagram must accurately tell the story and express the purpose of data analysis. In order to present meaningful data visualization, it is critical to understand the needs and expectations of an end-user’s sense of efficiency, effectiveness, and ease of use. We begin this process by first exploring the developer tools that aid in presenting data. By exploring different tools, we engage in preferences of users and highlight significant characteristics that represent effectiveness, efficiency, presentation layout and ease of use. Although research has shown preferences for types of visualizations (e.g., bar/line charts, colors, shapes, etc.) (Luo, Qin, Tang, & Li, 2018), there has been limited research investigating the preferred tool for presenting suc","cbCaivR0SSEB9SFx","https://ap.wps.com/l/cbCaivR0SSEB9SFx","pdf",1281305,16,"English","# Abstract\n# Introduction\n## Background on data visualization\n## Research questions and tool comparison\n# Related Work","[{\"question\":\"What problem does the study address about data analytics outputs?\",\"answer\":\"Most analysis results are presented as raw numbers that are hard for customers to interpret. Data visualization is used to present information in a visual, interactive, and meaningful form.\"},{\"question\":\"Which two visualization tools are compared in the research?\",\"answer\":\"The research compares Data-Driven Documents (D3.JS) and Google Charts for presenting retail customer data.\"},{\"question\":\"What do the study results suggest about tool performance and user preference?\",\"answer\":\"The results indicate D3.JS is more efficient, while Google Charts is more user friendly. The study also highlights that tool presentation and ease of use can affect users’ effectiveness, efficiency, and preference.\"}]","Towards Effective Customer Data Visualization - Data-Driven Documents (D3.JS) vs. Google Charts | PDF",1792984276]