Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Designed specifically for Azure, DQ on Demand™ boasts remarkable performance and scalability. Transitioning between data providers is seamless, allowing you to enhance your customer data with a pay-as-you-go model by directly accessing our DQ on Demand™ web services, which act as a user-friendly data quality marketplace. A wide array of data services is offered, such as data cleansing, enrichment, formatting, validation, verification, and transformations, among others. All you need to do is connect to our web-based APIs. This flexibility empowers you to switch data providers effortlessly, ensuring you have the freedom to choose what works best for your needs. You will also benefit from comprehensive developer documentation, ensuring a smooth integration process. You only pay for what you utilize, allowing you to purchase credits and allocate them as needed for various services. The setup process is straightforward and user-friendly. Additionally, all functionality of DQ on Demand™ can be easily integrated into Excel, providing a familiar low-code no-code solution. Moreover, you can guarantee your data is accurately cleansed within MS Dynamics using our DQ PCF controls, further enhancing your data management capabilities. This combination of features ensures that your data quality remains top-notch while maintaining operational efficiency.
Description
The Datagaps DataOps Suite serves as a robust platform aimed at automating and refining data validation procedures throughout the complete data lifecycle. It provides comprehensive testing solutions for various functions such as ETL (Extract, Transform, Load), data integration, data management, and business intelligence (BI) projects. Among its standout features are automated data validation and cleansing, workflow automation, real-time monitoring with alerts, and sophisticated BI analytics tools. This suite is compatible with a diverse array of data sources, including relational databases, NoSQL databases, cloud environments, and file-based systems, which facilitates smooth integration and scalability. By utilizing AI-enhanced data quality assessments and adjustable test cases, the Datagaps DataOps Suite improves data accuracy, consistency, and reliability, positioning itself as a vital resource for organizations seeking to refine their data operations and maximize returns on their data investments. Furthermore, its user-friendly interface and extensive support documentation make it accessible for teams of various technical backgrounds, thereby fostering a more collaborative environment for data management.
API Access
Has API
Yes
API Access
Has API
No
Screenshots View All
No images available
Integrations
AWS Marketplace
No
Cognism
Yes
D&B Direct
Yes
DataOps DataFlow
No
Datagaps ETL Validator
No
Loqate
Yes
Microsoft Azure
Yes
Microsoft Excel
Yes
Microsoft Power Apps
Yes
Integrations
AWS Marketplace
Yes
Cognism
No
D&B Direct
No
DataOps DataFlow
Yes
Datagaps ETL Validator
Yes
Loqate
No
Microsoft Azure
No
Microsoft Excel
No
Microsoft Power Apps
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
DQ Global
Founded
1997
Country
United Kingdom
Website
www.dqglobal.com/products/dq-on-demand/
Vendor Details
Company Name
Datagaps
Founded
2010
Country
United States
Website
www.datagaps.com
Product Features
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No
Product Features
Automated Testing
Hierarchical View
No
Move & Copy
No
Parameterized Testing
No
Requirements-Based Testing
No
Security Testing
No
Supports Parallel Execution
No
Test Script Reviews
No
Unicode Compliance
No
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No
ETL
Data Analysis
No
Data Filtering
No
Data Quality Control
No
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No