Text Analytics Market to 2025 – IBM Corporation, SAP SE, SAS Institute, Clarabridge, Expert Systems, OpenText Corp., Basis Technology, Linguamatics

The global text analytics market is expected to grow from US$ US$ 3.23 Bn in 2017 to US$ 18.28 Bn by 2025 at a CAGR of 24.2% between 2017 and 2025.

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.

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The key players profiled in the text analytics market report are

IBM Corporation,
SAP SE, SAS
Institute Inc.,
Clarabridge,
Expert Systems,
OpenText Corp.,
Basis Technology,
Linguamatics,
ANGOSS SOFTWARE CORPORATION
KNIME.

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.

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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

Reason to Buy:
- Save and reduce time carrying out entry-level research by identifying the growth, size, leading players and segments in the global Text Analytics Market
- 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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This release was published on openPR.