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Average Ratings 0 Ratings

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features
design
support

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Write a Review

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 No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

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

Integrations

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

Pricing Details

$0.04 per GB per hour
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

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 No 
Mac No 
Linux No 
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 No 
Live Training (Online) No 
In Person No 

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

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Integration

Dashboard No 
ETL - Extract / Transform / Load No 
Metadata Management No 
Multiple Data Sources No 
Web Services No 

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 

Alternatives

Alternatives

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