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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.

Media

Media

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

Categories and Features

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