Frequently Asked Questions

  • What are the current trends that are driving the text analytics market?
    The current and on going trends in text analytics are growing awareness, surge in data and increasing demand for real time analytics
  • In which vertical most of the industrial companies are deploying text analytics solutions?
    Text analytics is segmented on the basis of verticals. The industry verticals include BFSI, telecommunication & IT, retail and ecommerce, healthcare and life sciences, manufacturing, government and defense, energy and utilities, media and entertainment, travel and hospitality, and others (education, research, construction & outsourcing). The healthcare and life sciences segment is the fastest growing segment in the text analytics market due to the growing demand to tackle big data and deliver valuable insights from it.
  • Where will all these developments take the industry in the mid- to long-term?
    The text analytics market is projected to grow from $3.2 billion in 2016 To $8.8 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 17.2% during the forecast period.
  • Who are the top vendors in the market, and what is their competitive analysis?
    Major vendors in the global text analytics market include SAP SE (Walldorf, Germany), International Business Machines Corporation (New York, U.S.), SAS Institute, Inc. (North Carolina, U.S.), OpenText Corporation (Ontario, Canada), Clarabridge, Inc. (Virginia, U.S.), Megaputer Intelligence, Inc. (Indiana, U.S.), Luminoso Technologies, Inc. (Massachusetts, U.S.), MeaningCloud LLC (New York, U.S.), KNIME.com AG (Zurich, Switzerland), Infegy, Inc. (Missouri, U.S.), Lexalytics, Inc. (Massachusetts, U.S.), and Averbis (Freiburg Germany). These vendors have adopted various organic and inorganic growth strategies, such as new product launches, partnerships and collaborations, and mergers and acquisitions, to expand their presence in the global text analytics market further.
  • What are the drivers and challenges of the text analytics market?
    The major growth drivers of the market include the growing need for social media analytics, and increasing need of predictive analytics for businesses. The challenges faced are Lack of awareness, skilled workforce, and other operational challenges.

Text Analytics Software in Healthcare and Life Sciences

Comparing 29 vendors in Text Analytics Software across 126 criteria.
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SAP incorporates text analytics in its SAP HANA platform. SAP HANA platform offers comprehensive functionalities and is a suite comprising of linguistic, statistical, and machine learning capabilities. SAP HANA is helping companies accelerate their business processes by incorporating text analytics into a widely accepted platform. Text analytics provides a vast number of entity types and analysis rules, which help industries analyze text in a more comprehensive and detailed manner by making use of data obtained from text sources in multiple languages. The languages supported in a company’s text analytics software include Arabic, English, Dutch, Farsi, French, German, Italian, Japanese, Korean, Portuguese, Russian, simplified Chinese, Spanish, and traditional Chinese.
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The company offers the IBM SPSS Text Analytics for Surveys software, which assists organizations to transform their unstructured survey text into quantitative information and obtain insights through sentiment analysis solutions, thus accelerating business growth. The SPSS text analytics solution uses NLP specifically designed for survey text. SPSS Text Analytics for Surveys classifies responses and integrates results with other survey data for better insights and statistical analysis. It automates the classification process to remove the excess time and expenditure spent on manual coding. It uses linguistics-based technologies to diminish the ambiguities of human language, helping uncover patterns in the attitudes, beliefs, and opinions. SPSS Text Analytics for Surveys is a stand-alone program that works with IBM SPSS Statistics and other IBM SPSS products, which include IBM SPSS Custom Tables and software from the IBM SPSS Data Collection family.
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SAS provides a plethora of solutions related to text analytics with their product SAS text miner. The features that distinguish the SAS text miner from its competitors are as follows: Provisions to evaluate large data sets using high-performance text mining features. A user-friendly and flexible interface which conforms to Windows accessibility standards.
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Lexalytics, Inc. provides text and sentiment analysis software solutions for social media monitoring and brand reputation management. The company offers Salience Engine, a multi-lingual text analysis engine that is integrated into systems for BI. Salience supports text processing, natural language processing, and text analytics technologies, such as sentiment analysis.
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Dandelion API converts text to actionable data. It extracts meaning from unstructured text and puts it in context with a simple API. Dandelion API controls its underlying Knowledge Graph, without trusting traditional NLP channels. This makes it faster, extra-scalable, easier to customize, and natively language independent.

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Text meta-analysis is among the most critical business actions in modern database systems and business information systems. However due to its complex nature, it is not often incorporated. RapidMiner provides creative text analytics solutions that meet all the data needs of businesses where textual descriptions are present and need to be stored or examined.

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In the age of data and analytics, each and every organization has its own unique definitions, idioms, and language trends. MaritzCX Text Analytics ensures the capture of all the trends along with specific customizations that integrate words and phrases that apply specifically to products and industries across multiple languages. Users can instantaneously tap into all the investigation, skills, and knowledgeable capital.

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The text analytics solutions by MeaningCloud provide an entire package of advanced text analytics products, such as sentiment analysis, text classification, language identification, and topics extraction, which help analyze the unstructured data. Furthermore, the company offers add-ons for MS-Excel to facilitate text analytics from spreadsheets. The text analytics solutions offered by MeaningCloud comprise features, such as recognizing the structure of text, text clustering, text categorization, information extraction, and sentiment analysis. Sentiment analysis comprises applications of NLP, text analytics, and computational linguistics, which help identify and extract subjective information from various types of text.
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Infegy delivers products with an approach to address the challenges that organizations are facing. The company’s cloud-based social media intelligence platform, Infegy Atlas, uses an in-house NLP technology and was developed as an SaaS model to deliver real-time insights. Infegy Atlas simplifies the complex Boolean search queries using a predefined query builder, built-in error checking, and advanced filters that eliminate the need for additional operators.
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Squirro is an AI-based platform which uses machine learning to update users about the data and the next challenge. This platform helps a company to build better relationships with clients, partners, and predict the anomalies in the system and data automatically. This platform makes use of the 99% inactive data to offer insight-driven analytics.

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Knowliah provides a software solution that handles amorphous information and data, based on extremely innovative algorithms to clean intelligence and for the automatic enhancement of text through meta-data. Scripts, documents, and e-mails are repeatedly analyzed, augmented, and classified. The automation has helped users by enabling minimal manual intervention.

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The company entered the text analytics market with PolyAnayst, TextAnalyst, and X-SellAnalyst which are being widely accepted by establishments including federal organizations as their tools are powerful and automated, yet very simple to use. PolyAnalyst not only provides the drag and drop functionality for large volumes of structured data but also provides additional functionalities such as categorization, clustering, prediction, link analysis, keyword extraction, pattern discovery, and anomaly detection. TextAnalyst helps generate accurate summarization of text, retrieve semantic information by analyzing natural language queries, and extract relevant sentences from text-based documents.
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