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What is SAS Text Miner?

SAS Text Miner facilitates the extraction of valuable insights from diverse text documents, uncovering hidden themes and concepts. This tool adeptly combines quantitative information with unstructured text, effectively blending text mining with traditional data mining techniques. Being a part of the SAS® Enterprise Miner suite, it requires that SAS Enterprise Miner is installed on the same system to function properly. Furthermore, SAS High-Performance Text Mining can run on both a grid of computers or a single machine with multiple CPUs, making it flexible for various computing environments. The text algorithms used are optimized for multi-threading and operate in memory, which greatly improves both speed and efficiency while reducing input/output load. Users can access SAS Text Miner as nodes within the SAS High-Performance Data Mining framework or through the procedures PROC HPTMINE and PROC HPTMSCORE. To better understand SAS technology, individuals can take advantage of training courses provided by analytics experts, which will help them attain a thorough grasp of the available tools. Gaining expertise in these areas not only boosts one’s analytical skills but also enhances overall capabilities in data mining and analysis methodologies. Ultimately, mastering these techniques can empower users to make more informed decisions based on data-driven insights.

What is Data Miner?

Data Miner is recognized as a top-tier web scraping tool specifically designed for dedicated data mining experts. This extension works seamlessly with both Google Chrome and Edge, allowing users to effectively navigate web pages and extract valuable data into formats such as CSV or Excel files. With its intuitive interface, Data Miner streamlines the complex tasks of advanced data extraction and web crawling. Users can quickly take advantage of a rich library of over 60,000 data extraction rules included in the tool, or they can create custom rules to focus on specific information from web pages. Whether the task involves scraping a single page or an entire website, Data Miner is capable of retrieving a variety of data types, including search results, product information, prices, contact details, email addresses, and phone numbers. After the scraping is finished, the collected data is easily converted into a neatly organized CSV or Microsoft Excel file for straightforward downloading and use. Furthermore, Data Miner features a strong set of tools that enable users to pull any visible text from the webpage they are observing, significantly enhancing the flexibility and functionality of the tool. This makes it an invaluable resource for anyone seeking to perform comprehensive data extraction efficiently.

Media

Media

Integrations Supported

Google Chrome
Google Sheets
JavaScript
Microsoft Edge
Microsoft Excel

Integrations Supported

Google Chrome
Google Sheets
JavaScript
Microsoft Edge
Microsoft Excel

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$19.99 per month
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

SAS Institute

Date Founded

1976

Company Location

United States

Company Website

support.sas.com/en/software/text-miner-support.html

Company Facts

Organization Name

Data Miner

Company Location

United States

Company Website

dataminer.io

Categories and Features

Text Mining

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

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