Data Visualization Software Market: Quantitative Market Analysis, Current and Future Trends

Data Visualization refers to representation of data in a visual pattern so as to convey valuable information efficiently with the help of statistical graphs, charts, or infographics. Data Visualization software helps decision makers to analyze and easily comprehend huge amounts of data through interactive visualization tools.

This is done in the form of infographics, geographic maps, sparklines, heat maps and dials and gauges. Data visualization software helps end-users to save time by enabling quick decision-making by providing a multi-faceted view of business performance and operating dynamics. Currently, there is an imperative need to achieve a perfect balance between visual appeal and functionality so as to have optimum demand and use of the software at all levels of management and processes.

Rapid developments in the field of big data along with growing size and complexity of data has led to increased deployments of data visualization software globally. The incorporation of internet of things (IoT) in all aspects of business is adding to the increase in the number of data. This is further fuelling the need for organizing the data so as to derive valuable insights from it. Such requirements are driving the data visualization software market.

The rising need for decisions to be made in a short span of time requires tools to help derive analytical information from large chunks of unorganized data in a quick turn-around time. This is the major driving factor for rising demand in data visualization software. Technological advancements and flexibility in business intelligence solutions are paving the need for data integration and data analysis across varied industry sectors, this has led to the growing requirements of data visualization software for graphical representation purposes.

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However, the implementation of such software is complex and time consuming, thus hindering the growth of the market. Incorporating user-friendly data visualization tools in devices such as mobiles and tablets which can be used on-the-go can lead to time-saving and more convenience for higher management employees.

The global data visualization software market can be segmented on the basis of end-use industries, deployment model and geography. Based on end-use industries, the market can be divided into manufacturing, IT, healthcare, retail, banking and financial services, telecom and others. On the basis of deployment model, the data visualization software market can be segmented into on-premise, cloud-based and hybrid. Cloud-based deployment models are in demand owing to its convenience and easy accessibility.

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In terms of geography, the market can be segregated into North America, Europe, Asia Pacific, the Middle East and Africa and Latin America. North America is expected to leading the market during the forecast period owing to its growing use of big data and soaring implementation of IoT. Also, Asia Pacific region is anticipated to witness high growth over the forecast period owing to rising penetration of IT services and its recent developments.

Data visualization software developers are rapidly integrating real-time data analytics and predictive analytics features to reach out to a wider customer base. Some of the key players in the global data visualization software are International Business Machine, Tableau Software, Microsoft Corporation, Oracle Corporation, TIBCO Software Inc., QlikTech International AB, SAS Institute and SAP SE.

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The Internet of things (IoT) represents a giant network of interconnected devices or things that are embedded in the existing internet infrastructure. These things can include a variety of objects such as electronics devices, vehicles, equipment, sensors, and consumer appliances. The concept may signify the sharing of data and information with people and animals connected to the infrastructure in near-real time. The proliferation of connected devices and the soaring popularity of IoT among enterprises in developed and developing nations have led to the pressing need for Internet of Things testing mechanisms. Developing an effective IoT testing mechanism foregrounds evaluating key aspects such as compatibility and usability of the interconnected devices, security of the network, the connectivity, and overall performance of the system. Furthermore, enterprises implementing IoT should take into account the integration of new devices and technologies with the existing network. A number

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