Compare Amazon Comprehend vs. TIBCO Statistica

Amazon Comprehend is ranked 33rd in Data Science Platforms while TIBCO Statistica is ranked 22nd in Data Science Platforms. Amazon Comprehend is rated 0, while TIBCO Statistica is rated 0. On the other hand, Amazon Comprehend is most compared with Amazon SageMaker, whereas TIBCO Statistica is most compared with TIBCO Spotfire Data Science, IBM SPSS Statistics and IBM SPSS Modeler.
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Amazon Comprehend Logo
24 views|20 comparisons
TIBCO Statistica Logo
851 views|645 comparisons
Ranking
33rd
Views
24
Comparisons
20
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
22nd
Views
851
Comparisons
645
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: May 2020.
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Top Comparisons
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Compared 11% of the time.
Also Known As
Quest Statistica, Dell Statistica
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Overview

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. No machine learning experience required.

There is a treasure trove of potential sitting in your unstructured data. Customer emails, support tickets, product reviews, social media, even advertising copy represents insights into customer sentiment that can be put to work for your business. The question is how to get at it? As it turns out, Machine learning is particularly good at accurately identifying specific items of interest inside vast swathes of text (such as finding company names in analyst reports), and can learn the sentiment hidden inside language (identifying negative reviews, or positive customer interactions with customer service agents), at almost limitless scale.

Amazon Comprehend uses machine learning to help you uncover the insights and relationships in your unstructured data. The service identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text files by topic. You can also use AutoML capabilities in Amazon Comprehend to build a custom set of entities or text classification models that are tailored uniquely to your organization’s needs.

For extracting complex medical information from unstructured text, you can use Amazon Comprehend Medical. The service can identify medical information, such as medical conditions, medications, dosages, strengths, and frequencies from a variety of sources like doctor’s notes, clinical trial reports, and patient health records. Amazon Comprehend Medical also identifies the relationship among the extracted medication and test, treatment and procedure information for easier analysis. For example, the service identifies a particular dosage, strength, and frequency related to a specific medication from unstructured clinical notes.

Amazon Comprehend is fully managed, so there are no servers to provision, and no machine learning models to build, train, or deploy. You pay only for what you use, and there are no minimum fees and no upfront commitments.

TIBCO Statistica is a flexible analytics system, which allows users to: create analytic workflows that are packaged and published to business users, explore interactively and visualize problems and create and deploy statistical, predictive, data mining, machine learning, forecasting, optimization, and text analytic models. TIBCO Statistica advanced analytics and data science platform helps you to Embed Analytics Everywhere. TIBCO Statistica capabilities: Predictive Analytics, Provide broad access and data preparation everywhere, including for databases, cloud, and Apache Hadoop sources. Native Distributed Analytical Architecture (NDAA), Real-time Big-data Answers, Security and governance and Statistica works with R, Python, Scala scripts in-database or at the edge.
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Sample Customers
LexisNexis, Vibes, FINRA, VidMobDanske Bank
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: May 2020.
418,646 professionals have used our research since 2012.
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