Component technologies such as visualisation tools, modelling techniques and user interfaces have been heavily influencing the success of data visualisation (DV) solutions. As such, DV researchers and solution providers should form strategic alliances to drive advancements in component technologies. Only then can DV emerge as a holistic solution, which can deliver simplicity and a high level of user controllability. <\/p>\n<\/p>\n
New analysis from Frost & Sullivan, Data Visualisation - An Outlook on Disruptive Techniques (http:\/\/www.frost.com\/d549<\/a>), forecasts that the DV technology value chain will bring more application developers into its fold by adopting core software technologies with features such as high agnosticism, ability to integrate easily, and plug-in options for a wide range of applications. This, in turn, will enable faster diffusion of DV technologies across various application segments. <\/p>\n For instance, with its efficient interface that can deal with heavy numbers and algorithms to considerably reduce the load on big data analytics engines, DV is on the verge of becoming the most indispensable technology for big data solution providers. <\/p>\n \"Big data solution providers are beginning to realise the need for varied DV techniques to enhance their analytics capabilities,\" noted Technical Insights Senior Research Analyst Sathya Vendhan. \"Small- and medium-sized DV solution providers are therefore likely to strike collaboration deals with big data companies in the next three to six years.\" <\/p>\n The rapid increase of DV in small-screen mobile devices is also propelling solution providers to extend their reach beyond companies to the individual customer level. Small- and medium- sized DV technology providers will begin to occupy a major part of the market, as solutions evolve to provide interactive visuals on day-to-day activities, health conditions and other vital information. <\/p>\n \"DV solution providers will imbibe more customisation and personalisation techniques for product development,\" added Vendhan. \"To facilitate this transformation, DV research firms will create algorithms, which can be used in simple mobile devices as well as integrated in any sector-specific application.\" <\/p>\n So far, however, it has been difficult for DV application developers to convert general algorithms to application-specific functionalities due to compatibility issues. To overcome this issue, the majority of DV solution providers in the market are now using open source-based algorithms. <\/p>\n The challenges for DV hardware technology developers have been slightly different. For large-scale DV systems, hardware technology developers need to develop processors and servers that can support the charting engines seamlessly. Moreover, they have to ensure the availability of high-quality RAM, which is required to perform complex analytics. <\/p>\n Notwithstanding the market challenges, DV is expected to have the maximum impact on social networking. The technology's ability to provide a full view of even the minute details of activities in the social network medium has set it up to become the most needed medium for marketing, entertainment, governance and crime investigation as well. <\/p>\n <\/p>\n Read more from the original source: Component technologies such as visualisation tools, modelling techniques and user interfaces have been heavily influencing the success of data visualisation (DV) solutions. As such, DV researchers and solution providers should form strategic alliances to drive advancements in component technologies Continue reading
\nComprehend complex data sets through visual representations<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"