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What is OpenText Dimensions CM?
This approach facilitates simultaneous collaborative development, which minimizes rework, enhances visualization, mitigates conflict, and decreases team risk. Furthermore, it boosts team velocity and throughput, while maintaining the integrity of baseline configurations. It also simplifies processes such as rollback and recovery, streamlines approval workflows, and ensures consistency during automated build and deployment processes. Detecting issues early in the development lifecycle becomes significantly easier as well. Through the integration of tools like Pulse, problems can be pinpointed immediately upon code commitment. These actions promote a "shift left" philosophy by incorporating CI builds, unit testing, and code reviews. Additionally, the seamless integration with developer-friendly repositories and IDEs—such as Git, IntelliJ, Eclipse, and Microsoft.NET—coupled with comprehensive auditing, logging, immutable versioning, and detailed history, greatly reduces the time and effort required for regulatory compliance and audits. This thorough audit trail and tamperproof history not only streamline compliance but also enhance team accountability.
What is Deequ?
Deequ is a groundbreaking library designed to enhance Apache Spark by enabling "unit tests for data," which helps evaluate the quality of large datasets. User feedback and contributions are highly encouraged as we strive to improve the library. The operation of Deequ requires Java 8, and it is crucial to recognize that version 2.x of Deequ is only compatible with Spark 3.1, creating a dependency between the two. Users of older Spark versions should opt for Deequ 1.x, which is available in the legacy-spark-3.0 branch. Moreover, we also provide legacy releases that support Apache Spark versions from 2.2.x to 3.0.x. The Spark versions 2.2.x and 2.3.x utilize Scala 2.11, while the 2.4.x, 3.0.x, and 3.1.x releases rely on Scala 2.12. Deequ's main objective is to conduct "unit-testing" on data to pinpoint possible issues at an early stage, thereby ensuring that mistakes are rectified before the data is utilized by consuming systems or machine learning algorithms. In the upcoming sections, we will illustrate a straightforward example that showcases the essential features of our library, emphasizing its user-friendly nature and its role in preserving data quality. This example will also reveal how Deequ can simplify the process of maintaining high standards in data management.
Integrations Supported
Apache Spark
Eclipse IDE
Git
Microsoft 365
OpenText Dimensions RM
Integrations Supported
Apache Spark
Eclipse IDE
Git
Microsoft 365
OpenText Dimensions RM
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
OpenText
Date Founded
1991
Company Location
Canada
Company Website
www.opentext.com/products/dimensions-cm
Company Facts
Organization Name
Deequ
Company Website
github.com/awslabs/deequ
Categories and Features
Configuration Management
Access Control / Permissions
Application Deployment
Automated Provisioning
Infrastructure Automation
Node Management
Orchestration
Reporting Analytics / Visualization
Task Management