Data Visualization An Outlook on Disruptive Techniques (Technical Insights)

Transcription

1 Data Visualization An Outlook on Disruptive Techniques (Technical Insights) Comprehend Complex Data Sets through Visual Representations June 2014

2 Contents Section Slide Numbers 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 & Sullivan Story 43 2

3 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. 4

4 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. Data Visualization 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. 5

5 Research Methodology Technology Journals Periodicals Market Research Services Technology policy information sites Internal databases Thought Leader Briefings 1. Patent Review Technology Capabilities & Stakeholder Initiatives End User Analysis Secondary Research Innovators & Innovations 3. Assess Innovations Scenario Analysis Primary Research 2. Interview Participants Innovations Assessment Engineers CTOs/CEOs/CIOs Technical Architects Research Heads Strategic Decision Makers Technology Policy Heads Stakeholder Insights, Perspectives & Strategies OUTCOME -- FORECAST FUTURE OF TECHNOLOGY, MARKET ADOPTION & POTENTIAL APPLICATION SECTORS Source: Frost & Sullivan Analysis 6

6 Data Visualization Snapshot Data Visualization (DV) is usually a general way of talking about anything that converts data sources into a visual representation. This involves scientific and organizational information as well as general information. The representations can be made interactive with rich infographics. Forms of Data Visualization Time Series Maps Statistical Hierarchies Rich Contextual representation Increased interactivity Enables new inferences with different forms of interaction Strongly user controlled environment Networks Interactive Visualization Empowers organizations with strategic information 8

7 Data Visualization Snapshot -DV s purpose is to allow users to turn insights into actions (continued) Allows development of key business driving processes Establishing KPIs Define thresholds Interactive visualization leads to a defined action in achieving business success Insights into performance and organization s assets Selecting appropriate filters to present actionable date Allows development of insights through data Insights to action Application of tools and techniques for actionable intelligence Interactive visualization and analytics pave wave for real-time strategic decisions Identification of data hotspots Define trends Define relationship between multiple data streams Data correlation insights 9

8 Technology Value Chain Hardware Technology Operational Technology (Core Technology) Operational Technology(Applic ation Developers) End User Virtual Infrastructure Integration Hardware Developers Software Developers End Users Display Devices Core Technology Developer Application Developers Sectors Multi core servers Input and Output Devices Visualization tools Algorithms & Techniques Business Intelligence Mobile Apps Geospatial Information Banking and financial service Healthcare Retail Education Military Oil and Gas 10