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(Wireless-NewsWire.Com, March 16, 2018 ) Text analytics has become vigorous for smooth functionality of business. Text analytics is still mainly an undeveloped science and holds several different approaches. Text analytics has become increasing important in various purpose such as classification of information, sentimental analytics, and summarization of information and data investigation. It can be define as the process of analyzing retrieving of information from text sources. Text analytics is the processes of converting unstructured data into meaningful data for analysis. Text Analytics market is expected to grow US$ 18.28 Bn by 2025 from US$ 2.59 Bn in 2016.
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The text analytics market has experienced high growth and adoption in the last few years and is also expected to experience a significant growth and adoption in years to come. One of the major reason for high adoption of text analytics is, increasing competitive nature in business is making companies to seek for value added solutions. With increasing competition and changing consumer perspectives, organizations are making significant investments in solutions capable of analyzing customer and competitor data in order to improve competitiveness. The mainstream source of data are e-commerce platforms, social media, survey, individual blog, published articles and others. Greater part of data generated is unstructured, which makes it difficult and expensive for the companies to analyze with the help of individuals. This challenge combined with the rapid growth in data generation has led to the development of analytical tools not only capable of handling large volume of text data but also assist in better decision making. Text analytics software enables a user to draw meaning from large volume of data sets available from different sources.
In our study, we have segmented the text analytics market by deployment type, technology, applications and verticals. Text analysis is a process of transforming input text into series of terms, or canonical forms of words that are typically stripped of inflections and junk characters. Deployment of the text analysis is done in two types: on-premise and cloud-based. Multitenant architecture is very elastic, which necessitates on-demand provisioning and de-provisioning of applications and computing resources. This type of service is preferred by the countries that either do not have their data centers or have very classified data which cannot be shared over the cloud. Cloud-based text analysis are provided over the internet that are used by various companies for analysis of their data to collect necessary information regarding the data. On the basis of technology, text analytics can be distinguished into three types: natural language processing, automated machine learning and hybrid. Natural language processing is a scientific discipline that is concerned with making the natural language accessible to machines on the basis of text analytics. Automated machine learning promotes the development of malleable software packages which can be instantiated automatically in a data-driven way. It is a type of machine learning that can be used easily and without expert knowledge, whereas Hybrid is a mixture of NLP and Automated Machine Learning, which is required for the machine to perform the action based on commands or algorithms written in natural language
Text Analytics Market Key Players
IBM Corporation
SAP SE
SAS Institute Inc.
Clarabridge
Expert Systems
OpenText Corp.
Basis Technology
Linguamatics
ANGOSS SOFTWARE CORPORATION
KNIME
Reason to Buy
- Highlights key business priorities in order to assist companies to realign their business strategies.
- The key findings and recommendations highlight crucial progressive industry trends in the Text Analytics market, thereby allowing players to develop effective long term strategies.
- Develop/modify business expansion plans by using substantial growth offering developed and emerging markets.
- Scrutinize in-depth global market trends and outlook coupled with the factors driving the market, as well as those hindering it.
- Enhance the decision-making process by understanding the strategies that underpin commercial interest with respect to products, segmentation and industry verticals.
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