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What is OpenText Unstructured Data Analytics?

OpenTextâ„¢ offers Unstructured Data Analytics Products that harness the power of AI and machine learning to assist organizations in uncovering and utilizing vital insights concealed within various forms of unstructured data, including text, audio, videos, and images. By enabling organizations to connect data at scale, they can gain a clearer understanding of the context and content embedded in rapidly growing unstructured content. The platform provides unified analytics for text, speech, and video across more than 1,500 data formats, facilitating the extraction of insights from diverse media types. Utilizing technologies like OCR, natural language processing, and other advanced AI models allows organizations to monitor and interpret the essence of unstructured data effectively. Additionally, leveraging cutting-edge innovations in deep neural networks and machine learning enables a deeper comprehension of both spoken and written language found within the data, ultimately leading to the discovery of even greater insights. This comprehensive approach not only enhances data understanding but also empowers organizations to make more informed decisions based on the valuable information extracted from their unstructured data.

What is Hyland Document Filters?

Discover what firms like Cisco, Reveal Data, and Absolute Software have learned about Catalyst and similar products! Document Filters serves as an essential toolkit for facilitating file inspection and processing capabilities within applications for eDiscovery, data loss prevention, text analysis, and content management. It empowers users to search through, archive, and retrieve files efficiently. Are your users overwhelmed by the variety of file formats and the sheer volume of documents? We delve into how Document Filters enhances efficiency and delivers customer value, significantly benefiting all users in the process. Furthermore, Document Filters enables software developers to embed top-tier file identification features into their applications. By utilizing intelligent file identification, Document Filters effectively analyzes source content without solely depending on the filename extension, ensuring more accurate processing. This innovative approach not only streamlines workflows but also elevates the overall user experience.

Media

Media

Integrations Supported

.NET
Azure Marketplace
C
C#
C++
Hyland RPA
Java
Python

Integrations Supported

.NET
Azure Marketplace
C
C#
C++
Hyland RPA
Java
Python

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

OpenText

Date Founded

1991

Company Location

Canada

Company Website

www.opentext.com/products/unstructured-data-analytics

Company Facts

Organization Name

Hyland Software

Date Founded

1991

Company Location

United States

Company Website

www.hyland.com/en/solutions/products/document-filters

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Business Intelligence

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

Categories and Features

Document Management

Access Controls
Archiving & Retention
Collaboration Tools
Compliance Tracking
Document Archiving
Document Assembly
Document Capture
Document Conversion
Document Delivery
Document Indexing
Document Retention
Electronic Signature
Email Management
File Recovery
File Type Conversion
Forms Management
Full Text Search
Offline Access
Optical Character Recognition
Print Management
Version Control

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