IBM Rational Build Forge Integrations

CollabNet GitEye is a desktop for Git. It works with TeamForge, CloudForge and other Git services. GitEye combines a simple-to-use graphical Git client with central visibility into essential developer tasks such as defect tracking, Agile planning, code reviews and build services. GitEye is a graphical Git client for Windows, OSX and Linux. CollabNet GitEye provides a simple-to-use graphical Git client with central visibility into essential developer tasks such as defect tracking, agile planning, code reviews and build services. It’s easy to get started. GitEye works with multiple Git implementations including TeamForge, CloudForge and GitHub, and runs on most platforms. Say good-bye to the command line. Simple-to-use graphical Git client provides access to all vital Git functions including clone, commit, merge, rebase, push, fetch, pull, stash, stage, reset and more.

A data design solution that enables you to discover, model, relate, standardize and integrate diverse and distributed data assets throughout the enterprise. IBM InfoSphere® Data Architect is a collaborative enterprise data modeling and design solution that can simplify and accelerate integration design for business intelligence, master data management and service-oriented architecture initiatives. InfoSphere Data Architect enables you to work with users at every step of the data design process, from project management to application design to data design. The tool helps to align processes, services, applications and data architectures. Simple warehouse design, dimensional modeling and change management tasks help reduce development time and give you the tools to design and manage warehouses from an enterprise logical model. Time stamped, column-organized tables offer a better understanding of data assets to help increase efficiency and reduce time to market.

A Feature-based PLE Factory is much like a typical manufacturing factory except that it operates on digital assets rather than physical parts. To establish the factory, your organization creates a “superset” supply chain of digital assets that can be shared across the entire product line. These digital assets are equipped with all the feature options offered in the product line. The features chosen for each product are specified in the Bill-of-Features, then, a product asset instance is created by the Gears product configurator. The PLE Factory, based on Gears, becomes your automated production system for assembling and configuring the shared digital assets based on the features selected for each product variation, with the push of a button. With BigLever’s Gears, your organization has a common set of PLE concepts and constructs that augment your tools and assets, which allows engineering processes to flow cleanly and efficiently across the full lifecycle.

Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.