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What is DBF Sync?

If you are in search of a dependable method to consistently update or synchronize your DBF files, look no further than DBF Sync, which provides a comprehensive solution custom-designed to cater to your requirements! This tool stands out as both economical and indispensable, appealing to IT professionals, DBF system admins, and diverse database users who need regular data upkeep. One of the primary uses of DBF Sync is to refresh fields in a main file using information from an update file, with both sets of fields easily selectable within the software. Furthermore, DBF Sync allows users to establish projects that save configuration settings and file details for easy access in the future. In addition to its user-friendly wizard interface, the program offers a command line feature and can be configured for automatic operation through application schedulers, such as the Windows Scheduled Tasks utility. This capability makes it easy to integrate DBF Sync into your current data management workflows seamlessly. To further safeguard your data, DBF Sync also provides a simulation mode for testing actions before they are implemented, ensuring users can manage their database updates safely and without compromising data integrity. Overall, with these features, DBF Sync proves to be an invaluable tool for maintaining accurate and updated database files.

What is Anzo?

Anzo emerges as a groundbreaking platform focused on data discovery and integration, allowing users to seamlessly find, connect, and combine any enterprise data into analytics-ready datasets. Its innovative use of semantics and graph data models opens the door for a diverse range of individuals within an organization—from seasoned data scientists to novice business users—to engage in the data discovery and integration process, enabling them to build their own datasets for analysis. By leveraging graph data models, Anzo offers business users an intuitive visual representation of the enterprise's data environment, which simplifies navigation and understanding, even when faced with large, isolated, and complex datasets. The addition of semantics not only enhances the data with relevant business context but also helps users align data through shared definitions, allowing for the dynamic creation of integrated datasets that meet specific requirements. This approach promotes broader access to data and enhances its usability, cultivating a data-driven culture within organizations that encourages informed decision-making at all levels. Consequently, Anzo stands as a vital tool for enhancing collaboration and efficiency in data management across various departments.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

$29.95 per user
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

Astersoft Co

Company Location

Canada

Company Website

astersoft.com/en/dbfsync

Company Facts

Organization Name

Cambridge Semantics

Date Founded

2007

Company Location

United States

Company Website

www.cambridgesemantics.com/product/

Categories and Features

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Categories and 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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