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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Effortlessly extract, transform, and load (ETL) data for analytics and data science applications. Create seamless, code-free data flows directed towards data lakes and data marts. This functionality is included within Oracle’s extensive suite of integration tools. The user-friendly interface allows for easy configuration of integration parameters and automates the mapping of data between various sources and targets. You can utilize pre-built operators like joins, aggregates, or expressions to effectively manipulate your data. Central management of your processes enables the use of parameters to adjust specific configuration settings during runtime. Users can actively prepare their datasets and observe transformation results in real-time for process validation. Enhance your productivity and adjust data flows instantly, without needing to wait for execution completion. Additionally, this solution helps prevent broken integration flows and minimizes maintenance challenges as data schemas change over time, ensuring a smooth data management experience. This capability empowers users to focus on gaining insights from their data rather than grappling with technical difficulties.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

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

Integrations

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

Pricing Details

$0.04 per GB per hour
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/integration/oracle-cloud-infrastructure-data-integration/

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

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

Product Features

Data Science

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

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Integration

Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services

Product 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

Alternatives

Alternatives

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Kraken

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