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Text Analytics Market to Witness a Pronounce Growth During 2015-2021

Text Analytics Market to Witness a Pronounce Growth During

Text analytics can be defined as a process of retrieving information from the available text sources. Text analytics is used for various purposes such as summarization of information, classification, sentimental analysis and data investigation. Text Analytics has become vital for smooth functioning of business across world. Text Analytics software helps its end user to perform data analysis for obtaining useful insights. Text Analytics software’s are capable to process structured as well as unstructured data in a same efficient manner. In text analytics software, natural language processing toolkits are used which are competent enough to overcome any type of language barrier and this toolkit can derive information from any unknown languages. Modern text analytics software offers user friendly interface for better representation and analysis.

Globally, need of effective text analytics solution and services is increasing steadily. Factors which are driving the growth of global text analytics service market are growing demand of social media analysis for effective brand building, development of multilingual text analytics to overcome language barriers, increasing concern of financial frauds and growing big data market. On the other hand, factors which are restraining the growth of global text analytics market are lack of awareness among end users about software handling, high deployment cost and compliance issue with present IT infrastructure. However, added advantage of predictive analytics and credibility to analyse big data is expected to create great opportunity for text analytics market in future.

Global text analytics market is segmented on the basis of application, organization size, deployment model and verticals. On the basis of application, the global text analytics market can be segmented into, enterprise application, predictive analytics, data analytics application, web-based application, search based applications and others. Predictive analytics segment is expected to be major application segment of global text analytics market during the forecast period

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On the basis of organization size, the global text analytics market can be segmented into small enterprises, medium enterprises and large enterprises.

On the basis of deployment model, the global text analytics market can be segmented into on-premise and cloud deployment. Cloud based deployment model expected to gain significant importance during the period of forecast. However, small enterprises are still very much dependent on on-premise model

On the basis of verticals, the global text analytics market can be segmented into banking, financial serves and insurance (BFSI), healthcare & pharmaceuticals, manufacturing, retail & hospitality, telecommunication, consumer packed goods and others

On the basis of region, the text analytics market can be segmented into seven regions which includes, North America, Latin America, Western Europe, Asia-Pacific (excluding Japan), Eastern Europe, Japan and Middle East & Africa region. Further the market is sub-segmented as per the major countries of each region in order to provide better regional analysis of the Text Analytics Market. North America region is expected to dominate the global text analytics market during the period of forecast.

Western Europe region is expected to be second largest market in terms of revenue during the forecast period.

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Text Analytics Market: Key Players

Key players in global text analytics market are IBM Corporation, Microsoft, Hewlett-Packard Development Company, L.P., Attensity Inc., Clarabridge, SAP SE, TIBCO Software Inc., Tableau Software and Oracle among others. Key players are focusing on continuous innovations in the existing text analytics software’s. Hence new product launch is the major development strategy adopted by market players in order to grow in market. In 2014, Linguamatics launched I2E Semantic Enrichment to offer increased return on investment in enterprise search systems.

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