What is Safyr?

Safyr® dramatically reduces the time, costs, and resources required for discovering ERP metadata by as much as 90%. Users looking to effectively utilize metadata from leading ERP and CRM platforms such as SAP, Salesforce, Oracle, and Microsoft encounter three major obstacles that they must overcome first. If these challenges are not resolved quickly, they can result in project delays, rising expenses, failed deliveries, and in the worst cases, project cancellations. After identifying the essential metadata for your project, it is vital to utilize it for establishing various environments, which could involve data cataloging, governance systems, enterprise metadata management, data warehouses, ETL processes, or data modeling tools. The core aim behind the creation of Safyr® was to enable users to significantly enhance the value they gain from their initiatives that utilize data from major ERP and CRM systems, by offering effective and economical solutions to these hurdles. By optimizing the metadata discovery process, Safyr® allows organizations to concentrate more on achieving their primary goals, rather than being hindered by technical challenges. Ultimately, this enhancement in efficiency can lead to more successful project outcomes, fostering innovation and growth within the organization.

Pricing

Free Trial Offered?:
Yes

Integrations

Screenshots and Video

Company Facts

Company Name:
Silwood
Date Founded:
1992
Company Location:
United Kingdom
Company Website:
www.silwoodtechnology.com/safyr/

Product Details

Deployment
SaaS
Training Options
Documentation Hub
Online Training
Webinars
On-Site Training
Video Library
Support
Standard Support
Web-Based Support

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

Safyr Categories and Features

Data Discovery Software

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