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What is Oracle SQL Developer Data Modeler?

Oracle SQL Developer Data Modeler is a free graphical application that enhances productivity and simplifies data modeling tasks. This tool allows users to easily create, view, and adjust a range of models, such as logical, relational, physical, multi-dimensional, and data type models. It also supports both forward and reverse engineering processes, promoting collaboration with its integrated source code management features. Its flexibility enables deployment in both traditional and cloud environments. As a key component of the Oracle Database Tools suite, Oracle SQL Developer Data Modeler is recognized as a robust, standalone product that offers an extensive selection of data and database modeling resources. Moreover, users can access additional materials, including a general FAQ, on the Data Modeler homepage. This document seeks to provide clarity on various pricing-related questions that have surfaced in the community, offering valuable information to assist users in addressing these concerns effectively. By equipping users with this knowledge, the document aims to empower them in making informed decisions regarding their data modeling needs.

What is Oracle Machine Learning?

Machine learning uncovers hidden patterns and important insights within company data, ultimately providing substantial benefits to organizations. Oracle Machine Learning simplifies the creation and implementation of machine learning models for data scientists by reducing data movement, integrating AutoML capabilities, and making deployment more straightforward. This improvement enhances the productivity of both data scientists and developers while also shortening the learning curve, thanks to the intuitive Apache Zeppelin notebook technology built on open source principles. These notebooks support various programming languages such as SQL, PL/SQL, Python, and markdown tailored for Oracle Autonomous Database, allowing users to work with their preferred programming languages while developing models. In addition, a no-code interface that utilizes AutoML on the Autonomous Database makes it easier for both data scientists and non-experts to take advantage of powerful in-database algorithms for tasks such as classification and regression analysis. Moreover, data scientists enjoy a hassle-free model deployment experience through the integrated Oracle Machine Learning AutoML User Interface, facilitating a seamless transition from model development to practical application. This comprehensive strategy not only enhances operational efficiency but also makes machine learning accessible to a wider range of users within the organization, fostering a culture of data-driven decision-making. By leveraging these tools, businesses can maximize their data assets and drive innovation.

Media

Media

Integrations Supported

Oracle Database
Apache Hive
Apache Spark
Impala
Kinetica
MySQL
Oracle Cloud Infrastructure
Oracle SQL Developer
PwC Check-In

Integrations Supported

Oracle Database
Apache Hive
Apache Spark
Impala
Kinetica
MySQL
Oracle Cloud Infrastructure
Oracle SQL Developer
PwC Check-In

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/in/database/technologies/appdev/datamodeler.html

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

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

Categories and Features

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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