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Description

Machine learning reveals concealed patterns and valuable insights within enterprise data, ultimately adding significant value to businesses. Oracle Machine Learning streamlines the process of creating and deploying machine learning models for data scientists by minimizing data movement, incorporating AutoML technology, and facilitating easier deployment. Productivity for data scientists and developers is enhanced while the learning curve is shortened through the use of user-friendly Apache Zeppelin notebook technology based on open source. These notebooks accommodate SQL, PL/SQL, Python, and markdown interpreters tailored for Oracle Autonomous Database, enabling users to utilize their preferred programming languages when building models. Additionally, a no-code interface that leverages AutoML on Autonomous Database enhances accessibility for both data scientists and non-expert users, allowing them to harness powerful in-database algorithms for tasks like classification and regression. Furthermore, data scientists benefit from seamless model deployment through the integrated Oracle Machine Learning AutoML User Interface, ensuring a smoother transition from model development to application. This comprehensive approach not only boosts efficiency but also democratizes machine learning capabilities across the organization.

Description

Oracle SQL Developer Data Modeler is a complimentary graphical application designed to boost efficiency and streamline the process of data modeling. With this tool, users can effortlessly create, navigate, and modify various models, including logical, relational, physical, multi-dimensional, and data type models. The Data Modeler also offers capabilities for both forward and reverse engineering, while facilitating collaborative efforts through built-in source code management. It is versatile enough to be utilized in traditional setups as well as cloud-based environments. As part of the Oracle Database Tools suite, Oracle SQL Developer Data Modeler stands out as a comprehensive, independent product featuring a wide array of data and database modeling tools and utilities. Additional resources, including a general FAQ and other relevant materials, can be found on the Data Modeler homepage. This document aims to address some of the pricing-related inquiries that have emerged within the community, providing helpful insights for users navigating these questions.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Oracle Database Yes 
Apache Hive Yes 
Apache Spark Yes 
Impala Yes 
Kinetica Yes 
MySQL Yes 
Oracle Cloud Infrastructure Yes 
Oracle SQL Developer No 
PwC Check-In Yes 

Integrations

Oracle Database Yes 
Apache Hive No 
Apache Spark No 
Impala No 
Kinetica No 
MySQL No 
Oracle Cloud Infrastructure No 
Oracle SQL Developer Yes 
PwC Check-In No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/data-science/machine-learning/

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/in/database/technologies/appdev/datamodeler.html

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

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