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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 Acryl Data?

Address the challenge of neglected data catalogs with Acryl Cloud, which enhances the realization of value through Shift Left strategies tailored for data creators while providing an intuitive interface for users. This platform allows for the immediate identification of data quality concerns, automates anomaly detection to prevent future complications, and supports quick resolutions when issues do crop up. Acryl Cloud supports both push and pull methods for ingesting metadata, simplifying upkeep while ensuring the information remains trustworthy, up-to-date, and thorough. For smooth operations, data should work effortlessly. Go beyond basic visibility by utilizing automated Metadata Tests that continually uncover insights and highlight new avenues for improvement. By establishing clear asset ownership and applying automatic detection, efficient notifications, and temporal lineage for tracing the origins of issues, organizations can reduce confusion and shorten resolution times. Consequently, this leads to a more streamlined and productive data management framework, fostering a culture of continuous improvement and adaptability.

Media

Media

Integrations Supported

Amazon Redshift
Amazon SageMaker
Apache Airflow
Apache Hive
Apache Kafka
Apache NiFi
Apache Superset
ClickHouse
DataHawk
Databricks Data Intelligence Platform
Elasticsearch
Great Expectations
Looker
Metabase
Microsoft Teams
PostgreSQL
Presto
SAP HANA
Slack
dbt

Integrations Supported

Amazon Redshift
Amazon SageMaker
Apache Airflow
Apache Hive
Apache Kafka
Apache NiFi
Apache Superset
ClickHouse
DataHawk
Databricks Data Intelligence Platform
Elasticsearch
Great Expectations
Looker
Metabase
Microsoft Teams
PostgreSQL
Presto
SAP HANA
Slack
dbt

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

Acryl Data

Date Founded

2021

Company Website

www.acryldata.io

Categories and Features

Categories and Features

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

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