Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Safyr® significantly minimizes the time, expenses, and resources associated with discovering ERP metadata, achieving an impressive reduction of up to 90%. Before effectively utilizing metadata from prominent ERP and CRM solutions like SAP, Salesforce, Oracle, and Microsoft, users face three key obstacles that must be surmounted. Failing to address these challenges swiftly can lead to delays, increased costs, failures in delivery, and in severe situations, the cancellation of projects altogether. Once the necessary metadata is pinpointed for your initiative, it becomes crucial to leverage it for setting up additional environments, which may include data cataloging, governance platforms, enterprise metadata management, data warehouses, ETL processes, or data modeling tools. The primary goal of developing Safyr® was to empower users to significantly accelerate the value they derive from their projects, which incorporate data from major ERP and CRM systems, by providing efficient and cost-effective solutions to these challenges. By streamlining the metadata discovery process, Safyr® ensures that organizations can focus more on their core objectives rather than getting bogged down by technical issues.
API Access
Has API
API Access
Has API
Integrations
AWS Glue
AWS Lake Formation
Alation
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Collibra
ER/Studio Enterprise Edition
IBM Cloud
IDERA Precise for Databases
Integrations
AWS Glue
AWS Lake Formation
Alation
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Collibra
ER/Studio Enterprise Edition
IBM Cloud
IDERA Precise for Databases
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
Silwood
Founded
1992
Country
United Kingdom
Website
www.silwoodtechnology.com/safyr/
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