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What is Qualdo?

We specialize in providing Data Quality and Machine Learning Model solutions specifically designed for enterprises operating in multi-cloud environments, alongside modern data management and machine learning frameworks. Our advanced algorithms are crafted to detect Data Anomalies across various databases hosted on Azure, GCP, and AWS, allowing you to evaluate and manage data issues from all your cloud database management systems and data silos through a unified and streamlined platform. Quality perceptions can differ greatly among stakeholders within a company, and Qualdo leads the way in enhancing data quality management by showcasing issues from the viewpoints of diverse enterprise participants, thereby delivering a clear and comprehensive understanding. Employ state-of-the-art auto-resolution algorithms to effectively pinpoint and resolve pressing data issues. Moreover, utilize detailed reports and alerts to help your enterprise achieve regulatory compliance while simultaneously boosting overall data integrity. Our forward-thinking solutions are also designed to adapt to shifting data environments, ensuring you remain proactive in upholding superior data quality standards. In this fast-paced digital age, it is crucial for organizations to not only manage their data efficiently but also to stay ahead of potential challenges that may arise.

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.

Media

Media

No images available

Integrations Supported

AWS Marketplace
Amazon Web Services (AWS)
DataOps DataFlow
Datagaps ETL Validator
Google Cloud Platform
Microsoft Azure

Integrations Supported

AWS Marketplace
Amazon Web Services (AWS)
DataOps DataFlow
Datagaps ETL Validator
Google Cloud Platform
Microsoft Azure

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

Qualdo

Company Location

United States

Company Website

www.qualdo.ai/

Company Facts

Organization Name

Datagaps

Date Founded

2010

Company Location

United States

Company Website

www.datagaps.com

Categories and Features

Data Quality

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

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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

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