The global data visualization market, valued at $9.84 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 10.95% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across various industries necessitates effective visualization tools for insightful analysis and decision-making. Furthermore, the rising adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, driving market growth. Advances in artificial intelligence (AI) and machine learning (ML) are integrating seamlessly with data visualization platforms, enhancing automation and predictive capabilities, further stimulating market demand. The BFSI (Banking, Financial Services, and Insurance) sector, along with IT and Telecommunications, are major adopters, leveraging data visualization for risk management, fraud detection, customer relationship management, and network optimization. However, challenges remain, including the need for skilled professionals to effectively utilize these tools and concerns regarding data security and privacy. The market segmentation reveals a strong presence of executive management and marketing departments across organizations, highlighting the strategic importance of data visualization in business operations. The market's competitive landscape is characterized by established players like SAS Institute, IBM, Microsoft, and Salesforce (Tableau), along with emerging innovative companies. This competition fosters innovation and drives down costs, making data visualization solutions more accessible to a broader range of businesses and organizations. Regional variations in market penetration are expected, with North America and Europe currently holding significant shares, but Asia Pacific is poised for substantial growth, driven by rapid digitalization and technological advancements in the region. The on-premise deployment mode still holds a considerable market share, though the cloud/on-demand segment is experiencing faster growth due to its inherent advantages. The ongoing trend towards self-service business intelligence (BI) tools is empowering end-users to access and analyze data independently, increasing the overall market demand for user-friendly and intuitive data visualization platforms. Future growth will depend on continued technological advancements, expanding applications across diverse industries, and addressing the existing challenges related to data skills gaps and security concerns. This report provides a comprehensive analysis of the Data Visualization Market, projecting robust growth from $XX Billion in 2025 to $YY Billion by 2033. It covers the period from 2019 to 2033, with a focus on the forecast period 2025-2033 and a base year of 2025. This in-depth study examines key market segments, competitive landscapes, and emerging trends influencing this rapidly evolving industry. The report is designed for executives, investors, and market analysts seeking actionable insights into the future of data visualization. Recent developments include: September 2022: KPI 360, an AI-driven solution that uses real-time data monitoring and prediction to assist manufacturing organizations in seeing various operational data sources through a single, comprehensive industrial intelligence dashboard that sets up in hours, was recently unveiled by SymphonyAI Industrial., January 2022: The most recent version of the IVAAP platform for ubiquitous subsurface visualization and analytics applications was released by INT, a top supplier of data visualization software. IVAAP allows exploring, visualizing, and computing energy data by providing full OSDU Data Platform compatibility. With the new edition, IVAAP's map-based search, data discovery, and data selection are expanded to include 3D seismic volume intersection, 2D seismic overlays, reservoir, and base map widgets for cloud-based visualization of all forms of energy data.. Key drivers for this market are: Cloud Deployment of Data Visualization Solutions, Increasing Need for Quick Decision Making. Potential restraints include: Lack of Tech Savvy and Skilled Workforce/Inability. Notable trends are: Retail Segment to Witness Significant Growth.

Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.

GLOBE provides the ability to view and interact with data measured across the world. Select the visualization tool to map, graph, filter and export data that have been measured across GLOBE protocols since 1995. Currently the GLOBE Data Visualization Tool supports a subset of protocols. Additional Features and capabilities are continually being added.

The Flood Inundation Mapping (FIM) Visualization Deck is a web-based application designed to display and compare flood extent and depth information across various temporal and scenario conditions. It provides a front-end interface for accessing geospatial flood data and interacting with mapped outputs generated from hydraulic modeling.

Core Functions: • Flood Extent Mapping: Visualizes flood extents from modeled scenarios (e.g., 2-year, 10-year, 100-year events) and real-time conditions based on streamflow observations or forecasts. • Flood Depth Visualization: Displays depth rasters over affected areas, derived from hydraulic simulations (e.g., HEC-RAS). • Scenario Comparison: Allows side-by-side viewing of multiple FIM outputs to support calibration or decision analysis. • Layer Management Toolbox: Users can toggle basemaps, adjust layer transparency, load datasets, and control map extents.

Data Inputs: • Precomputed flood inundation extents (raster/tile layers) • Depth grids • Stream gauge metadata • Associated hydraulic model outputs

Technical Stack: • Front-end: Built with JavaScript, primarily using Leaflet.js for interactive map rendering. • Back-end Services: Uses GeoServer to serve raster tiles and vector layers (via WMS/WFS). Uses OGC-compliant services and REST endpoints for data queries. • Data Formats: Raster layers (e.g., GeoTIFF, PNG tiles), vector layers (GeoJSON, shapefiles), elevation models, and model-derived grid outputs. • Database: Integrates with a PostgreSQL/PostGIS backend or similar spatial database for hydrologic and geospatial data management. • Deployment: Hosted via University of Iowa infrastructure, with modular UI elements tied to specific watersheds or study areas.

Intended Use: The application provides a reference and exploratory tool for comparing modeled flood scenarios, visualizing extent and depth data, and interacting with region-specific inundation data products.

This map contains summary data meant to be visualized within the National Coral Reef Monitoring Program's Data Visualization Tool.This map and its associated data/dashboards/hub are developed to represent data in both the Atlantic and Pacific basins and all four monitoring themes (Socioeconomic, Benthic, Fish and Climate). Each dashboard presents data at a resolution that is appropriate for the sampling method and effort for each area. Users can filter the data by a number of variables to allow them to refine the graphs and charts. Additionally, users can download the summary data tables for their own analyses. The metadata for the data in this application can be found at https://www.ncei.noaa.gov/data/oceans/coris/library/NOAA/CRCP/monitoring/metadata/This map is dependent upon the following AGOL items:NCRMP_Prod_gdb Feature Layer (hosted) NCRMP_Prod_gdb File Geodatabase The following AGOL items are dependent upon this map:NCRMP Data Visualization Tool Hub Site Application NCRMP Data Visualization Tool Hub Initiative NCRMP Pacific Fish Dashboard Web Experience NCRMP Pacific Fish Embed Dashboard

This tutorial will teach you how to take time-series data from many field sites and create a shareable online map, where clicking on a field location brings you to a page with interactive graph(s).

The tutorial can be completed with a sample dataset (provided via a Google Drive link within the document) or with your own time-series data from multiple field sites.

Part 1 covers how to make interactive graphs in Google Data Studio and Part 2 covers how to link data pages to an interactive map with ArcGIS Online. The tutorial will take 1-2 hours to complete.

An example interactive map and data portal can be found at: https://temple.maps.arcgis.com/apps/View/index.html?appid=a259e4ec88c94ddfbf3528dc8a5d77e8

NDS is an interactive, web-based system, for the visualization of multidimensional neighborhood dynamics across the 50 largest US Metropolitan Statistical Areas (MSAs) from 1980 to 2010 (http://neighborhooddynamics.dreamhosters.com). Four different visualization tools are developed: (1) an interactive time slider to show neighborhood classification changes for different years; (2) multiple interactive bar charts for each variables of each neighborhood; (3) an animated neighborhood’s trajectory and sequence cluster on a self-organizing map (SOM) output space; and (4) a synchronized visualization tool showing maps for four time stamps at once. The development of this interactive online platform for visualizing dynamics overcomes many of the challenges associated with communicating changes for multiple variables, across multiple time stamps, and for a large geographic area when relying upon static maps. The system enables users to select and dive into details on particular neighborhoods and explore their changes over time.

This map contains summary data meant to be visualized within the National Coral Reef Monitoring Program's Data Visualization Tool.This map and its associated data/dashboards/hub are developed to represent data in both the Atlantic and Pacific basins and all four monitoring themes (Socioeconomic, Benthic, Fish and Climate). Each dashboard presents data at a resolution that is appropriate for the sampling method and effort for each area. Users can filter the data by a number of variables to allow them to refine the graphs and charts. Additionally, users can download the summary data tables for their own analyses. The metadata for the data in this application can be found at https://www.ncei.noaa.gov/data/oceans/coris/library/NOAA/CRCP/monitoring/metadata/This map is dependent upon the following AGOL items:NCRMP_Prod_gdb Feature Layer (hosted) NCRMP_Prod_gdb File Geodatabase The following AGOL items are dependent upon this map:NCRMP Data Visualization Tool Hub Site Application NCRMP Data Visualization Tool Hub Initiative NCRMP Socioecon Dashboard Web Experience NCRMP Socioecon Embed Dashboard

This dataset can be used to create a Tile map for India in a Visualization Tool. Dataset was created by me while making a Visualization on Tableau.

The MAPS dataset is for the research community. It provides a very in-depth and detailed analysis of Android applications to extract an enhanced set of features. The MAPS dataset relies on a diverse dataset collected from different repositories, containing more than 153000 applications (>2TB in size). It outputs more than 40000 features for analysis and training of deep neural network models.

The DC Office of Zoning (OZ) proudly announces an expansion of its online mapping services with the release of the DCOZ 3D Zoning Map. This new mapping application builds off existing DC Open Datasets and new OZ Zoning data to visualize the District in 3D, providing greater context for proposed development projects and helping enhance Board of Zoning Adjustment and Zoning Commission decisions throughout the District. The 3D Zoning Map was developed to enhance District resident’s understanding, knowledge, and participation in Zoning matters, and help increase transparency in the Zoning process.

Data visualization plays a vital role in modern scientific communication across diverse domains, shaping the understanding of complex information through color choices. However, the significance of color palette selection goes beyond aesthetics and scientific communication, encompassing accessibility for all, especially individuals with color vision deficiencies. To address this challenge, we introduce "Color Quest," an intuitive Shiny app that empowers users to explore color palettes for data visualization while considering inclusivity. The app allows users to visualize palettes across various types of plots and maps envisioning how they appear to individuals with color blindness. In addition, it enables users to visualize palettes on their own custom-uploaded images. This short communication presents the app’s design, interactive interface, and transformative potential in enhancing data visualization practices. Developed using open-source standards, Color Quest aligns with accessibility discussions, offering a practical tool and platform for raising awareness about inclusive design. Its open-source nature fosters transparency, community collaboration, and long-term sustainability. Color Quest’s practicality renders it indispensable for scientific domains, simplifying palette selection and promoting accessibility. Its impact extends beyond academia to diverse communication settings, harmonizing information dissemination, aesthetics and accessibility for more impactful scientific communication.

This web map is a component of the CrowdMag Visualization App.NOAA's CrowdMag is a crowdsourced data collection project that uses a mobile app to collect geomagnetic data from the magnetometers that modern smartphones use as part of their navigation systems. NCEI collects these data from citizen scientists around the world and provides quality control services before making them available through a series of aggregated maps and charts. These data have the potential to provide a high resolution alternative to geomagnetic satellite data, as well as near real-time information about changes in the magnetic field.This map shows data collected from phones around the world! Displayed are the Crowdsourced magnetic data within a tolerance level of prediction by World Magnetic Model. We have added some uncertainty to each data point shown to ensure the privacy of our contributors. The data points are grouped together (or "aggregated") into small areas , and we display the median data value across all the readings for each point.

This map is updated every day. Layers are available for Median Intensity, Median Horizontal Component (Y), and Median Vertical Component (Z).


Use the time slider to select the date range. Select the different layers under the "Crowdmag Observations" menu. View a color scale using the legend tool. Zoom to your location using the "Find my Location" tool. Click or tap on a data point to view a popup containing more information.

Customer Journey Mapping Software Market size was valued to be USD 10.8 Billion in the year 2024 and it is expected to reach USD 53.6 Billion in 2032, at a CAGR of 13.8% over the forecast period of 2026 to 2032.

Customer Journey Mapping (CJM) software is a specialist application that helps organizations see and analyze the various stages of a customer's interaction with a firm. This program delivers a full and comprehensive perspective of the customer experience from the first contact to the final encounter allowing businesses to optimize their operations and increase overall customer satisfaction

. The essence of CJM software is its capacity to record and map out the customer journey in a visual manner such as a flowchart or diagram which aids in identifying pain points, understanding customer wants, and aligning business goals appropriately.

The primary application of customer journey mapping software is to improve customer experience (CX). Understanding the various stages and touchpoints of the customer journey allows firms to discover pain points and areas for improvement. For example, if a customer journey map shows that consumers regularly abandon their shopping carts at the payment stage, the company can investigate and fix the problem whether by streamlining the checkout process, providing clearer instructions, or offering more payment options.

CJMS will use advanced analytics to deliver more detailed insights into client behavior and preferences. The integration of big data and predictive analytics will enable organizations to anticipate client wants and identify possible problems before they arise. This proactive strategy will allow businesses to modify their services and interactions in real-time resulting in a smooth and rewarding consumer experience. Businesses will obtain a holistic picture of the consumer journey by analyzing massive volumes of data from multiple touchpoints revealing patterns and trends that can be used to guide strategic choices and optimize marketing efforts.

Enhanced Attention to Customer Experience (CX): The importance of delivering superior customer experiences for sustaining brand loyalty and boosting revenue is increasingly acknowledged by businesses. The ability of customer journey mapping software to enable businesses to pinpoint and refine customer interaction points throughout their journey is leading to enhanced CX and competitive differentiation.

Embracing Omnichannel Marketing: The engagement of modern consumers with brands through diverse platforms (including websites, social media, and mobile apps) is noted. The tracking of these multi-channel interactions and the understanding of customer behavior facilitated by customer journey mapping software assist in tailoring marketing efforts for better engagement.

The Requirement for Insights Based on Data: The necessity for insights driven by data in comprehending customer behavior and preferences is recognized by businesses. Through the aggregation and examination of customer information from various sources, customer journey mapping software offers critical insights for augmenting customer engagement and loyalty.

Regulatory Compliance Demands: Certain sectors are governed by regulations that enforce data privacy and security standards. Tools for meticulous tracking and management of customer information are provided by customer journey mapping software aiding businesses in meeting these regulatory requirements.

Increased Utilization Among SMBs: The adoption of customer journey mapping software previously more common among larger corporations, is now expanding to Small and Medium Businesses (SMBs). The appeal of this technology to a broader business spectrum is being enhanced by cloud-based solutions and subscription models.

Mapping Software Market Outlook

According to our latest research, the global mapping software market size reached USD 8.2 billion in 2024. Driven by accelerating digital transformation across industries, the market is poised for robust expansion, with a projected CAGR of 13.7% from 2025 to 2033. By the end of 2033, the mapping software market is forecasted to attain a value of USD 25.2 billion. This remarkable growth trajectory is underpinned by the increasing integration of geospatial data analytics, the proliferation of smart city initiatives, and the surging demand for real-time location intelligence across sectors such as transportation, urban planning, and disaster management.

One of the primary growth drivers for the mapping software market is the rapid adoption of geospatial technologies in both public and private sectors. Organizations are leveraging mapping software to enhance operational efficiency, optimize resource allocation, and gain actionable insights from complex spatial datasets. For example, the transportation and logistics industry relies heavily on mapping solutions for route optimization, fleet management, and real-time tracking, which significantly reduces operational costs and improves delivery timelines. Additionally, government agencies utilize mapping software for urban planning, land administration, and disaster response, enabling data-driven decision-making and more effective public service delivery. The continuous evolution of mapping software, with features such as 3D visualization, artificial intelligence integration, and cloud-based collaboration, is further catalyzing market growth.

Another significant factor propelling the mapping software market is the proliferation of Internet of Things (IoT) devices and the exponential growth of location-based services. The integration of IoT with mapping software enables real-time data collection and visualization, which is critical for applications such as smart cities, environmental monitoring, and asset tracking. Enterprises are increasingly adopting mapping solutions to visualize IoT sensor data on interactive maps, facilitating predictive maintenance, energy management, and risk assessment. Moreover, the rise of mobile mapping applications and the widespread availability of high-speed internet connectivity have democratized access to mapping technologies, empowering small and medium enterprises (SMEs) to harness spatial intelligence for business growth and innovation.

The mapping software market is also benefiting from strong investments in infrastructure development and the rising need for disaster management solutions. Governments and urban planners are deploying advanced mapping tools to model urban growth, assess environmental impact, and plan resilient infrastructure. In regions prone to natural disasters, mapping software plays a crucial role in risk assessment, emergency response coordination, and post-disaster recovery. The integration of satellite imagery, drone data, and real-time analytics is enhancing the accuracy and timeliness of mapping outputs, making them indispensable for disaster preparedness and mitigation. As climate change and urbanization continue to pose complex challenges, the demand for sophisticated mapping software is expected to escalate further.

Mapping and Navigation Software is increasingly becoming an integral component of the geospatial technology landscape. These software solutions are designed to provide precise navigation and mapping capabilities, which are essential for a wide range of applications, from urban planning to autonomous vehicle navigation. The ability to integrate real-time data from multiple sources, such as GPS, IoT devices, and satellite imagery, allows for the creation of dynamic and interactive maps that enhance situational awareness and decision-making. As industries continue to adopt digital transformation strategies, the demand for advanced mapping and navigation software is expected to grow, driving innovation and competition in the market. These solutions not only improve operational efficiency but also enable organizations to gain a competitive edge by leveraging spatial intelligence.

Regionally, North America leads the mapping software market, accounting for the largest share due to its early adoption of advanced geospatial technologies and the presence of major industry players. However, Asia Pacific is emerging as the

HazMatMapper is an online and interactive geographic visualization tool designed to facilitate exploration of transnational flows of hazardous waste in North America (http://geography.wisc.edu/hazardouswaste/map/). While conventional narratives suggest that wealthier countries such as Canada and the United States (US) export waste to poorer countries like Mexico, little is known about how waste trading may affect specific sites within any of the three countries. To move beyond anecdotal discussions and national aggregates, we assembled a novel geographic dataset describing transnational hazardous waste shipments from 2007 to 2012 through two Freedom of Information Act requests for documents held by the US Environmental Protection Agency. While not yet detailing all of the transnational hazardous waste trade in North America, HazMatMapper supports multiscale and site-specific visual exploration of US imports of hazardous waste from Canada and Mexico. It thus enables academic researchers, waste regulators, and the general public to generate hypotheses on regional clustering, transnational corporate structuring, and environmental justice concerns, as well as to understand the limitations of existing regulatory data collection itself. Here, we discuss the dataset and design process behind HazMatMapper and demonstrate its utility for understanding the transnational hazardous waste trade.

When creating choropleth maps, mapmakers often bin (i.e. group, classify) quantitative data values into groups to help show that certain areas fall within a similar range of values. For instance, a mapmaker may divide counties into groups of high, middle, and low life expectancy (measured in years). It is well known that different binning methods (e.g. natural breaks, quantiles) yield different groupings, meaning the same data can be presented differently depending on how it is divided into bins. To help guide a wide variety of users, we present a new, open-source, web-based, geospatial visualization tool, Exploropleth, that lets users interact with a catalog of established data binning methods, and subsequently compare, customize, and export custom maps. This tool advances the state of the art by providing multiple binning methods in one view and supporting administrative unit reclassification on-the-fly. We interviewed 16 cartographers and geographic information systems (GIS) experts from 13 government organizations, non-government organizations (NGOs), and federal agencies who identified opportunities to integrate Exploropleth into their existing mapmaking workflow, and found that the tool has the potential to educate students as well as mapmakers with varying levels of experience. Exploropleth is open-source and publicly available at https://exploropleth.github.io.