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OpsHub Integration Manager

No-code integration platform for rich bi-directional sync

OpsHub Migration Manager

Zero downtime migration to tool of your choice

OpsHub Archive Manager

Keep Historical Data, Without Slowing Down Your Tools

OpsHub Migrator for Microsoft Azure DevOps

Migrate or restructure Azure DevOps

OpsHub Data Bridge

Real-time, context-rich data lake for AI or analytics

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 By Role

DevOps Leaders

Accelerate delivery with clear insights

DevOps Leaders

Accelerate delivery with clear insights

Digital Engineering or Transformation Leaders

Transform smarter with a connected digital thread

Enterprise Architects

Confident transitions for every enterprise change

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Operational readiness through connected engineering

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Modernize and move to cloud without disruption

Digital Thread and Compliance

Build a compliant digital thread for complex environments

Smart Engineering for AI, Co-Pilot Initiatives

Build the foundation for smarter AI

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Software Development & Agile Engineering

No-code integration across teams and systems

IT Service Management & Customer Support

Enable collaboration between IT, support, and business teams

Product Lifecycle Management & Systems Engineering

Connect PLM & engineering teams for smarter products

Requirements Management for Regulated Industries

Ensure regulatory compliance from start to release

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DevOps Analytics

The Need for DevOps Analytics

Data in the digital world is increasingly becoming disparate in nature due to use of multiple, heterogeneous types of systems. It is impossible to manually aggregate all these data, analyze them, and learn from them. While the possibilities for utilizing the data in a productive manner is immense, the system disparities within the ALM & DevOps ecosystem hinder the utilization. A huge volume of data trapped in system silos leads to significant delays in identifying opportunities, problems, and trends. Data silos and system incompatibilities also obstruct real-time reporting and analytics. With the creation of a Data Lake, enterprises will be able to leverage cross-domain contextual data in multiple beneficial manners.

How Data Lake is Beneficial for an Enterprise

Comprehensive Reporting and Analytics

Data Lake stores all data regardless of the source and structure. This means that enterprises can easily apply different types of analytics and create a comprehensive data reporting mechanism by working on a single data source repository.

Compliance Audits

With access to all data from a central place, it is easier for enterprise to adhere to the compliance requirements. End-to-end traceability for all data and related historical information allows enterprise to be compliance-audit-ready always.

Accelerate Functionality with Artificial Intelligence

The teaming-up of Data Lake and Artificial Intelligence can infuse enterprises with accelerated functionality. Data Lake aids in extracting hidden business insights and further provides agility by augmenting Artificial Intelligence to foresee trends and value from raw data as well.

OpsHub Helps Enterprises Create a Unified and Perceptive Ecosystem

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