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Average Ratings 0 Ratings

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ease
features
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support

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Description

Amazon DataZone serves as a comprehensive data management solution that empowers users to catalog, explore, share, and regulate data from various sources, including AWS, on-premises systems, and third-party platforms. It provides administrators and data stewards with the ability to manage and oversee data access with precision, guaranteeing that users possess the correct level of permissions and contextual understanding. This service streamlines data access for a diverse range of professionals, such as engineers, data scientists, product managers, analysts, and business users, thereby promoting insights driven by data through enhanced collaboration. Among its notable features are a business data catalog that enables searching and requesting access to published datasets, tools for project collaboration to oversee and manage data assets, a user-friendly web portal offering tailored views for data analysis, and regulated data sharing workflows that ensure proper access. Furthermore, Amazon DataZone leverages machine learning to automate the processes of data discovery and cataloging, making it an invaluable resource for organizations striving to maximize their data utility. As a result, it significantly enhances the efficiency of data governance and utilization across various business functions.

Description

Anzo is an innovative platform for data discovery and integration that empowers users to locate, connect, and blend various enterprise data into datasets that are ready for analysis. With its distinctive application of semantics and graph data models, Anzo enables individuals across the organization—from expert data scientists to inexperienced business users—to actively participate in the data discovery and integration journey, crafting their own analytics-ready datasets in the process. The graph data models offered by Anzo create a visual representation of enterprise data, simplifying the navigation and understanding of complex and siloed information. By incorporating semantics, Anzo enriches the data with business context, allowing users to unify data according to shared definitions and create blended datasets that are tailored for immediate business needs. This democratization of data access not only fosters collaboration but also accelerates decision-making across various levels of the organization.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

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

Integrations

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

Pricing Details

No price information available.
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

Amazon

Founded

1998

Country

United States

Website

aws.amazon.com/datazone/

Vendor Details

Company Name

Cambridge Semantics

Founded

2007

Country

United States

Website

www.cambridgesemantics.com/product/

Product 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

Product 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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