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What is Informatica Data Quality?

Gain immediate strategic benefits by providing extensive support that meets the changing requirements of data quality for various users and data types through automation powered by AI. Whether your organization is involved in data migration or sophisticated analytics, Informatica Data Quality supplies the necessary adaptability to implement data quality seamlessly in any situation. By empowering business users, you can also improve collaboration between IT departments and business executives. Maintain oversight of data quality across both multi-cloud and on-premises environments for a wide range of applications and workloads. Incorporate human intervention within the workflow, allowing business users to evaluate, modify, and authorize exceptions during the automated process as needed. Execute data profiling and ongoing analysis to uncover relationships and more efficiently pinpoint problems. Utilize AI-generated insights to automate vital tasks and enhance data discovery processes, which in turn increases productivity and operational efficiency. This all-encompassing strategy not only improves data quality but also encourages a culture of ongoing enhancement throughout the organization, ultimately positioning your business for future growth and success.

What is DQOps?

DQOps serves as a comprehensive platform for monitoring data quality, specifically designed for data teams to identify and resolve quality concerns before they can adversely affect business operations. With its user-friendly dashboards, users can track key performance indicators related to data quality, ultimately striving for a perfect score of 100%. Additionally, DQOps supports monitoring for both data warehouses and data lakes across widely-used data platforms. The platform comes equipped with a predefined list of data quality checks that assess essential dimensions of data quality. Moreover, its flexible architecture enables users to not only modify existing checks but also create custom checks tailored to specific business requirements. Furthermore, DQOps seamlessly integrates into DevOps environments, ensuring that data quality definitions are stored in a source repository alongside the data pipeline code, thereby facilitating better collaboration and version control among teams. This integration further enhances the overall efficiency and reliability of data management practices.

Media

Media

Integrations Supported

Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Airflow
Apache Spark
Google Cloud BigQuery
Google Cloud Platform
Looker
MySQL
Oracle Database
PostgreSQL
Presto
SQL Server
SingleStore
Slack
Snowflake
Trino
Visual Studio Code
Wiiisdom Ops
dbt

Integrations Supported

Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Airflow
Apache Spark
Google Cloud BigQuery
Google Cloud Platform
Looker
MySQL
Oracle Database
PostgreSQL
Presto
SQL Server
SingleStore
Slack
Snowflake
Trino
Visual Studio Code
Wiiisdom Ops
dbt

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$499 per month
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

Informatica

Date Founded

1993

Company Location

United States

Company Website

www.informatica.com/products/data-quality.html

Company Facts

Organization Name

DQOps

Date Founded

2021

Company Location

Poland

Company Website

dqops.com

Categories and Features

Data Quality

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

Categories and Features

Data Quality

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

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