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What is Oracle Data Miner?

Oracle Data Miner enables data scientists, "citizen data scientists," and both business and data analysts to engage with data directly within the database using a user-friendly graphical interface that features a "drag and drop" workflow editor. As an enhancement to Oracle SQL Developer, Oracle Data Miner (ODMr) adeptly captures and visually presents the analytical steps that users undertake while exploring data and developing machine learning models. The workflows established using ODMr are crucial for not only reapplying analytical techniques but also for fostering knowledge exchange among team members. Additionally, ODMr generates SQL and PL/SQL scripts seamlessly and offers a workflow API that aids in the efficient deployment of models throughout the organization. This capability significantly reduces data movement, ensures scalability for large datasets, upholds security, and accelerates the transition from model creation to implementation. By adopting this advanced methodology, organizations can better leverage their data resources, ultimately resulting in smarter decision-making and enhanced business performance. Furthermore, this systematic approach helps to create a culture of data-driven insights that can transform strategic initiatives.

What is Keel?

KEEL, which stands for Knowledge Extraction based on Evolutionary Learning, is an open-source software tool developed in Java and licensed under GPLv3, aimed at supporting a wide range of knowledge data discovery tasks. It features a user-friendly graphical interface that prioritizes data flow, allowing users to create experiments that utilize different datasets and computational intelligence algorithms, particularly those based on evolutionary strategies, to assess their performance. The software offers a broad spectrum of standard knowledge extraction methodologies, as well as data preprocessing techniques—such as training set selection, feature selection, discretization, and imputation for missing values—alongside various computational intelligence learning algorithms, hybrid models, and statistical methods for comparing experimental results. This all-encompassing toolkit enables researchers to perform in-depth analyses of novel computational intelligence strategies against traditional approaches. Moreover, KEEL has been intentionally designed to fulfill two main objectives: to promote research advancement and to improve educational experiences in the domain of knowledge discovery. Its adaptability and functionality make it an essential tool for both scholarly pursuits and real-world applications in the field of knowledge extraction. Ultimately, the ongoing development of KEEL ensures that it remains relevant and effective for its users.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

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

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/database/technologies/datawarehouse-bigdata/dataminer.html

Company Facts

Organization Name

Keel

Company Website

www.keel.es/

Categories and Features

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

Categories and Features

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

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