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What is rudol?

You can integrate your data catalog seamlessly, minimize communication challenges, and facilitate quality assurance for all employees in your organization without the need for any installation or deployment. Rudol serves as a comprehensive data platform that empowers businesses to comprehend all their data sources, independent of their origin. By streamlining communication during reporting cycles and addressing urgent issues, it also promotes data quality assessment and the proactive resolution of potential problems for every team member. Every organization can enhance their data ecosystem by incorporating sources from Rudol's expanding roster of providers and standardized BI tools, such as MySQL, PostgreSQL, Redshift, Snowflake, Kafka, S3, BigQuery, MongoDB, Tableau, and PowerBI, with Looker currently in development. Regardless of the source of the data, anyone within the company can effortlessly locate where it is stored, access its documentation, and reach out to data owners through our integrated solutions. This ensures that the entire organization stays informed and connected, fostering a culture of data-driven decision-making.

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

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Integrations Supported

Amazon Redshift
Apache Airflow
Google Cloud BigQuery
Looker
MySQL
PostgreSQL
Snowflake
Amazon Athena
Amazon Web Services (AWS)
Azure Databricks
Google Cloud Platform
Microsoft Azure
Microsoft Power BI
MongoDB
Oracle Database
Presto
SingleStore
Slack
Trino
dbt

Integrations Supported

Amazon Redshift
Apache Airflow
Google Cloud BigQuery
Looker
MySQL
PostgreSQL
Snowflake
Amazon Athena
Amazon Web Services (AWS)
Azure Databricks
Google Cloud Platform
Microsoft Azure
Microsoft Power BI
MongoDB
Oracle Database
Presto
SingleStore
Slack
Trino
dbt

API Availability

Has API

API Availability

Has API

Pricing Information

$0
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

rudol

Date Founded

2021

Company Location

Argentina

Company Website

rudol.ai

Company Facts

Organization Name

DQOps

Date Founded

2021

Company Location

Poland

Company Website

dqops.com

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

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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