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  3. > Data Visualization - An Outlook on Disruptive Techniques (Technical Insights)

Technology Mutations Meet Business Demands

In today’s business world where industries are suffering from information overload and data glut, there remains a need for a solution which could simplify the task in helping the user to comprehend the information available and also quicken the process. Data visualization serves as a solution which would help find hidden patterns and trends in the data that could be pivotal in making business decisions. Businesses and organizations have recognized the importance of data visualization technology and hence have started identifying and investing in suitable data visualization tools.

Research Outline
Data visualization (DV) refers to latest and futuristic advancements where representation of huge amounts of data is done with interactive and user-friendly visualization. This is achieved by support of evolving technologies. New technologies and applications are evolving in this space to make an effective contribution to big data, social networking, and mobile data.
In brief, this research service provides the following:
- A brief snapshot of data visualization.
- Investment scenario in data visualization.
- Corporate activities in data visualization.
- Prominent models in data visualization.
- Drivers for specific technology markets.
- Convergence of component technology innovations.
- Choicest technology mutations for specific business needs.

Key Findings
Data visualization (DV) is heavily influenced by its component technologies. These technologies include visualization tools, modeling techniques, and user interfaces. It is necessary that DV researchers and solution providers should form strategic alliances to bring in simultaneous advancements in these component technologies. This in turn would facilitate development of DV as a holistic solution, which can deliver simplicity and a high level of user controllability.

The technology value chain of DV is expected to bring in to its fold more application developers by bringing in core software technologies with abilities, such as high agnosticism, ability to integrate easily, and easier plug in options for a wide range of applications. This in turn is expected to enable faster diffusion of DV.

The rapid increase of DV in small screen mobile devices is expected to help the reach of DV to the individual customer. The solutions could be evolved to provide interactive visuals about day to day activities, health conditions, and so on. This in turn would give rise to more small- and medium-sized DV solution providers occupying the major part of the DV market.

Small- and medium-sized DV solution providers are expected to get in to collaboration deals with big data companies in a medium term of 3 to 6 years. This is mainly due to big data solution providers realizing the need for varied DV techniques to enhance their analytics capabilities.

Table Of Contents

Data Visualization - An Outlook on Disruptive Techniques (Technical Insights)
Executive Summary 3

Research Outline 4

Key Findings 5

Research Methodology 6

Data Visualization Gains Prominence 7

Convergence of Component Technology Innovation 13

Data Visualization Investment Scenario 23

Convergence Scenario 27

Choicest Technology Specification meets Business needs 33

Analyst Insights 40

Key Contacts 41

The Frost and Sullivan Story 43

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