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Top Text Analytics Companies in Boston


Is it difficult to perform text analytics out of huge piles of text-based content? No more! Business Agencies curates a list of Top Text Analytics Companies in Boston that can drive your way through the chaos of social media and review sites for greater engagements and results. In the overwhelming age of social media, special text analytics solutions are designed to Looking patterns and trends in consumer behaviors from various textual platforms such as comments, reviews, blogs and more. These data-led insights can be leveraged from designing to branding your products. Furthermore, of all the text mining companies servicing in the market, it becomes difficult to Looking the Top. So Business Agencies in Boston researches and curates a list with service details and client reviews of each one. Following is the list of the Top text analytics service providers:

1 Companies

profile

Datamatics

No Reviews

Datamatics provides intelligent solutions for data-driven businesses to increase productivity and enhance the customer experience. With a complete digital approach, Datamatics portfolio spans across Information Technology Services, Web Development, Mobile App Development, Market research, Business Process Management, Engineering Services and Big Data & Analytics all powered by Artificial Intelligence. It has established products in Robotic Process Automation, Intelligent Document Processing, Business Intelligence and Automated Fare Collection. Datamatics services global customers across Banking, Financial Services, Insurance, Healthcare, Manufacturing, International Organizations, and Media & Publishing. The Company has presence across 4 continents with major delivery centers in the USA, IRead More

  • dollar

    $25-49/hr

  • user

    1000+

  • calender

    1975

  • location

    United States (USA)

Frequently Asked Questions

Text analytics is the process of extracting meaningful information from large amounts of unstructured text data using computer algorithms and natural language processing techniques.

Text analytics focuses specifically on unstructured text data, while other types of data analysis in Big Data may deal with structured numerical data or other data formats.

Common applications include sentiment analysis, customer feedback analysis, social media monitoring, content categorization, and trend identification in large text datasets.

Text analytics can help businesses gain insights from customer feedback, improve product development, enhance customer service, and make data-driven decisions based on textual information from various sources.

Challenges include dealing with unstructured data, handling multiple languages, interpreting context and nuances in text, and managing large volumes of data efficiently.

Text analytics can process much larger volumes of data more quickly than traditional methods, and can uncover insights from natural language that may be missed by surveys or focus groups.

Skills typically include programming (often Python or R), understanding of natural language processing, knowledge of machine learning algorithms, and familiarity with big data technologies.

Accuracy can vary depending on the quality of data, the algorithms used, and the specific task. While not perfect, modern text analytics tools can achieve high levels of accuracy for many applications.

Yes, many text analytics tools support multiple languages, but the effectiveness can vary. Some languages may require specialized tools or additional processing steps.

Text analytics is often one component of a larger Big Data strategy, complementing other types of data analysis to provide a more complete picture of customer behavior, market trends, and business operations.

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