Content analytics softwares uses natural language queries, trends analysis, predictive analytics and contextual discovery to reveal trends and patterns for the company’s unstructured data.
Valley Cottage, NY -- (SBWIRE) -- 03/14/2017 -- Content Analytics comprises of range of search and reporting technologies which can provide identical levels of business intelligence and strategic value for unstructured data. Content analytics for unstructured information includes social media monitoring, reputation monitoring, and sentiment analysis. Content analytics softwares uses natural language queries, trends analysis, predictive analytics and contextual discovery to reveal trends and patterns for the company's unstructured data.
Discovery tools are the search tools that analyse contents for its likely relevancy to a process, by linking names, time periods or terms used. Discovery tools can also extend to legal hold and partitioning of content for further scrutiny. Various types of discovery tools include search engines, auto-categorization, and information visualization tools.
Cognitive computing softwares make context computable by identifying and extracting context features such as hour, location, task, history or profile in structured way for an individual or an application engaged in a specific process at definite time and place. Cognitive computing technologies and platforms includes expert assistance software.
Content Analytics, Discovery and Cognitive Systems, collectively covers the market and technologies that access, analyse, organize, and provides advisory services related to a range of unstructured data. Cognitive systems leverages large amounts of structured and unstructured data and content analytics tools, along with several infrastructure technologies to answer questions, provide recommendations and directions. In addition to this, it helps in hypothesis and formulation of possible answers and updates itself by adopting learning algorithms from its mistake and failures.
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Global Market of Content Analytics, Discovery and Cognitive Software: Drivers and Restraint
Unstructured data is driving a revitalisation in the analysis of information, resulting in the introduction of innovative tools capable to offer intelligent assistance, guidance and recommendations to customers. Particularly, cognitive systems offer cloud and mobile-based platforms through which theintelligent assistants (such as Apple's Siri, Google's Google Now, Amazon Echo, Microsoft's Cortana, Brainasoft's Braina, Samsung's S Voice, LG's Voice Mate, BlackBerry's Assistant, SILVIA, HTC's Hidi, IBM's Watson) are able to operate, using databases and knowledge graphs built with the help of content analytics.
Content analytics, discovery and cognitive Systems, together are used for complex applications such as medical research, fraud prevention, digital forensics for crime detection and sentiment analytics to measure the "feelings of the crowd" towards a brand or product. These tools matches structured database information with unstructured data of documents to rearrange the data in the organized form. Additionally, it analyses text usage, patterns in video or sound.
Content analytics along with discovery tools and cognitive systems can create relevant cost and consumption metrics and facilitate improved information lifecycle management (ILM) chains for End-users. This will enable the End-users to identify the potential value of digital content and will aid them in understanding the significance of their investment in the storage and future analytics.
As these technologies are still at the nascent stage, promoting the significance of this technology is currently a major challenge for the market participants. anticipating the unknowns as past based predictions have their limitations (in case of predictive analysis), Growing popularity of e-discovery, Digital Asset Management (DAM), Web Analytics and De-duplication technologies are acting as a potential substitute for the techniques including sentiment analysis, copyright detection and digital forensics used in content analytics
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Global Market of Content Analytics, Discovery and Cognitive Software: Segmentation
Segmentation on the basis of product type:
Various type of products in this market include: Test softwares (in multiple languages) and rich media tagging (audio, video, and image), software for searching, information discovery, machine learning, deep learning, hypothesis generation, entity and relationship extraction, supervised and unsupervised learning, clustering, categorization, question answering, filtering, alerting, visualization and navigation.
Segmentation on the basis of end-user:
Various end-users of the market include: government & public services, Finance, Banking & Insurance sector, utilities, telecommunication operator, IT & High-Tech ECM provider, healthcare & pharmaceutical sector, media & web publishing, retail, transport and real estate.
Finance, banking and insurance and utilities, are currently witnessing higher adoption of content analytics softwares. The factors driving this higher adoption are: Growing need for real-time response requirements in banking, increasingly stringent regulatory environment and the need to mitigate risk, demanding customer profile and growing competitive pressure, exploding data volumes & growing complexity, in the BFSI sector.
Global Market of Content Analytics, Discovery and Cognitive Software: Key Players
Some of the prominent players in the content analytics, discovery and cognitive software market include: IBM Inc., Hewlett-Packard Company, Baidu Inc., Elastic GmbH, Facebook Inc., Google Inc., LucidWorks Inc., Microsoft Corporation, and Wipro Limited.