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What is Oracle Enterprise Metadata Management?

Oracle Enterprise Metadata Management (OEMM) is a powerful solution designed for the effective management of metadata. It can harvest and catalog metadata from numerous sources, including relational databases, Hadoop environments, ETL processes, business intelligence systems, and data modeling tools. OEMM does more than simply store metadata; it also enables users to interactively search and browse through the data, while providing essential features like data lineage tracking, impact analysis, and the analysis of both semantic definitions and usage for every asset in its catalog. Utilizing advanced algorithms, OEMM seamlessly integrates metadata from various providers, resulting in a detailed view of the data's journey from its initial source to its final presentation or report. The platform supports a wide range of metadata sources, encompassing data modeling tools, databases, CASE tools, ETL engines, data warehouses, BI systems, and EAI environments, among others. This broad compatibility allows organizations to efficiently manage their metadata across multiple environments. Ultimately, OEMM empowers businesses to maximize the value of their data assets, enhancing decision-making and operational efficiency.

What is Anzo?

Anzo emerges as a groundbreaking platform focused on data discovery and integration, allowing users to seamlessly find, connect, and combine any enterprise data into analytics-ready datasets. Its innovative use of semantics and graph data models opens the door for a diverse range of individuals within an organization—from seasoned data scientists to novice business users—to engage in the data discovery and integration process, enabling them to build their own datasets for analysis. By leveraging graph data models, Anzo offers business users an intuitive visual representation of the enterprise's data environment, which simplifies navigation and understanding, even when faced with large, isolated, and complex datasets. The addition of semantics not only enhances the data with relevant business context but also helps users align data through shared definitions, allowing for the dynamic creation of integrated datasets that meet specific requirements. This approach promotes broader access to data and enhances its usability, cultivating a data-driven culture within organizations that encourages informed decision-making at all levels. Consequently, Anzo stands as a vital tool for enhancing collaboration and efficiency in data management across various departments.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

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/middleware/technologies/enterprise-metadata-management.html

Company Facts

Organization Name

Cambridge Semantics

Date Founded

2007

Company Location

United States

Company Website

www.cambridgesemantics.com/product/

Categories and Features

Categories and Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

Data Fabric

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Integration

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

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