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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.

What is Oracle Cloud Infrastructure Data Flow?

Oracle Cloud Infrastructure (OCI) Data Flow is an all-encompassing managed service designed for Apache Spark, allowing users to run processing tasks on vast amounts of data without the hassle of infrastructure deployment or management. By leveraging this service, developers can accelerate application delivery, focusing on app development rather than infrastructure issues. OCI Data Flow takes care of infrastructure provisioning, network configurations, and teardown once Spark jobs are complete, managing storage and security as well to greatly minimize the effort involved in creating and maintaining Spark applications for extensive data analysis. Additionally, with OCI Data Flow, the absence of clusters that need to be installed, patched, or upgraded leads to significant time savings and lower operational costs for various initiatives. Each Spark job utilizes private dedicated resources, eliminating the need for prior capacity planning. This results in organizations being able to adopt a pay-as-you-go pricing model, incurring costs solely for the infrastructure used during Spark job execution. Such a forward-thinking approach not only simplifies processes but also significantly boosts scalability and flexibility for applications driven by data. Ultimately, OCI Data Flow empowers businesses to unlock the full potential of their data processing capabilities while minimizing overhead.

Media

Media

Integrations Supported

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

Integrations Supported

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

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$0.0085 per GB per hour
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/data-science/machine-learning/

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/big-data/data-flow/

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

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Science

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

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