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What is Datagaps DataOps Suite?

The Datagaps DataOps Suite is a powerful platform designed to streamline and enhance data validation processes across the entire data lifecycle. It offers an extensive range of testing solutions tailored for functions like ETL (Extract, Transform, Load), data integration, data management, and business intelligence (BI) initiatives. Among its key features are automated data validation and cleansing capabilities, workflow automation, real-time monitoring with notifications, and advanced BI analytics tools. This suite seamlessly integrates with a wide variety of data sources, which include relational databases, NoSQL databases, cloud-based environments, and file systems, allowing for easy scalability and integration. By leveraging AI-driven data quality assessments and customizable test cases, the Datagaps DataOps Suite significantly enhances data accuracy, consistency, and reliability, thus becoming an essential tool for organizations aiming to optimize their data operations and boost returns on data investments. Additionally, its intuitive interface and comprehensive support documentation ensure that teams with varying levels of technical expertise can effectively utilize the suite, promoting a cooperative atmosphere for data management across the organization. Ultimately, this combination of features empowers businesses to harness their data more effectively than ever before.

What is Data Bridge?

Brave River's ETL solution, referred to as Data Bridge, allows users to extract data from diverse sources and then reformat and process it before transferring it to a specified destination file. This multi-step methodology utilized by Data Bridge significantly mitigates the financial burdens and errors commonly associated with manual data input. In contrast to typical ETL tools that simply collect, format, and transmit data, Data Bridge elevates the process by allowing users to manipulate and preserve data, performing numerous transactions prior to the final loading phase. With the ability to apply a limitless variety of transformation stages, users can ensure that their data remains impeccably formatted throughout the entire ETL process. This robust functionality not only simplifies data management but also enhances overall efficiency when dealing with extensive datasets, making it an invaluable asset for organizations looking to optimize their data workflows. Furthermore, the versatility of Data Bridge empowers users to adapt their data handling approach to meet specific business needs effectively.

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Integrations Supported

AWS Marketplace
DataOps DataFlow
Datagaps ETL Validator

Integrations Supported

AWS Marketplace
DataOps DataFlow
Datagaps ETL Validator

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Datagaps

Date Founded

2010

Company Location

United States

Company Website

www.datagaps.com

Company Facts

Organization Name

Brave River Solutions

Date Founded

1999

Company Location

United States

Company Website

www.braveriver.com/blog/data-bridge-custom-etl-software/

Categories and Features

Automated Testing

Hierarchical View
Move & Copy
Parameterized Testing
Requirements-Based Testing
Security Testing
Supports Parallel Execution
Test Script Reviews
Unicode Compliance

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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