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What is CERF ELN?

CERF offers cost-effective solutions for data management and oversight tailored for laboratories, businesses, or organizations. The core component of the system is the CERF server, which can be deployed either on-premises or on platforms such as Amazon or any other preferred hosting service. Scientists and managers can easily and securely access the data housed on the CERF server through complimentary Macintosh and iOS client applications. These client apps provide unparalleled access to data, enabling users to store, retrieve, share, and locate files while also managing, categorizing, and organizing their ongoing research details efficiently. A wide array of import and export functionalities is available for transferring various types of data into and out of CERF. Furthermore, CERF’s sophisticated semantic meta technologies ensure that even many years later, your downstream audience can effectively interpret and utilize your data. This comprehensive approach to data management not only enhances research collaboration but also supports long-term data integrity and accessibility.

What is Amazon DataZone?

Amazon DataZone serves as a robust data management solution, enabling users to efficiently catalog, discover, and share data sourced from AWS, on-premises systems, and external third-party platforms. It provides administrators and data stewards with essential tools to implement precise access controls, ensuring users obtain the appropriate permissions and relevant information. By simplifying data access for professionals such as engineers, data scientists, product managers, analysts, and business users, it encourages data-driven decision-making through improved collaboration. Key features include a business data catalog that aids in searching and requesting access to published data, project collaboration tools that help manage data assets effectively, a user-friendly web portal offering customized views for data analysis, and structured workflows for data sharing that uphold necessary access levels. Furthermore, Amazon DataZone utilizes machine learning to streamline the discovery and cataloging processes, greatly improving operational efficiency. This groundbreaking service not only simplifies the management of data but also cultivates a culture of insight-driven decisions throughout organizations, ultimately leading to enhanced productivity and innovation.

Media

Media

Integrations Supported

AWS Glue
AWS Lake Formation
Amazon Athena
Amazon Redshift
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)

Integrations Supported

AWS Glue
AWS Lake Formation
Amazon Athena
Amazon Redshift
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

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

Lab-Ally

Date Founded

2013

Company Location

United States

Company Website

lab-ally.com

Company Facts

Organization Name

Amazon

Date Founded

1998

Company Location

United States

Company Website

aws.amazon.com/datazone/

Categories and Features

Document Management

Access Controls
Archiving & Retention
Collaboration Tools
Compliance Tracking
Document Archiving
Document Assembly
Document Capture
Document Conversion
Document Delivery
Document Indexing
Document Retention
Electronic Signature
Email Management
File Recovery
File Type Conversion
Forms Management
Full Text Search
Offline Access
Optical Character Recognition
Print Management
Version Control

Categories and Features

Data Discovery

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

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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