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What is Spectrum Quality?

Gather, normalize, and standardize your information from various sources and formats. It is vital to ensure that all forms of data, whether related to companies or individuals, are normalized, irrespective of being structured or unstructured. This task utilizes sophisticated supervised machine learning techniques grounded in neural networks to grasp the complexities and variations found in different types of information while automating the parsing of data. Spectrum Quality stands out as a reliable partner for international clients who require comprehensive data standardization and transliteration across various languages, including culturally nuanced terms in Arabic, Chinese, Japanese, and Korean. Our advanced text-processing capabilities enable the extraction of insights from any natural language input and efficiently classify unstructured text. By leveraging pre-trained models in conjunction with machine learning algorithms, you can pinpoint entities and tailor your models to clearly define specific entities pertinent to any domain or category, thereby boosting the overall adaptability and applicability of the data processing solutions we provide. Consequently, clients can enjoy a more streamlined and effective approach to data management and analysis, leading to improved decision-making processes. This holistic approach not only enhances data quality but also fosters better insights, driving business success.

What is Azure Text Analytics?

Harness natural language processing to gain valuable insights from unstructured text without requiring any machine learning knowledge, by utilizing an array of features from the Cognitive Services for Language. Elevate your understanding of customer emotions through sentiment analysis and identify key phrases and entities such as people, places, and organizations to uncover common themes and patterns. Use specialized, pretrained models to classify medical terminology specific to various fields. Evaluate text across multiple languages and reveal essential concepts within the content, which include key phrases and named entities that highlight individuals, events, and organizations. Delve into customer feedback regarding your brand while examining sentiments linked to specific topics through opinion mining techniques. Additionally, derive critical insights from unstructured clinical documents, including doctors' notes, electronic health records, and patient intake forms, by applying text analytics tailored for healthcare settings, ultimately enhancing patient care and informing decision-making processes. By integrating these advanced capabilities, organizations can stay ahead of trends and better meet the needs of their stakeholders.

Media

Media

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

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

Precisely

Date Founded

1968

Company Location

United States

Company Website

www.precisely.com/product/precisely-spectrum-quality/spectrum-quality

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

Categories and Features

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Categories and Features

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

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