Technical Briefs

Microsoft SSIS and SQL Server 2012, 2014 for Data Virtualization

Microsoft has a broad range of tools and capabilities, some overlapping Enterprise Enabler, although data virtualization, and bi-directional data virtualization across multiple disparate systems are not among them. Advances in SSIS and SQL Server are improving the abilities for data integration with these tools, however, the ease of use for complex integrations, particularly data virtualization fall short of Enterprise Enabler’s (EE’s) scope and time to production…

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Data Virtualization Reduces Synchronization Volumes

Data synchronization evolved roughly in parallel to data integration. As soon as there were two applications that were inter-dependent from a data perspective, the data had to be shared (integration) and the shared data needed to be the same in both applications (synchronization). The problem was addressed several ways over time, initially with bulk uploads, later by attempting to rewrite all applications to use a shared database, and then with messaging systems such as publish/subscribe technologies…

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Enterprise Enabler in an IBM Environment

Stone Bond’s Enterprise Enabler® (EE) agile integration platform offers all modes of integration in a single platform. One hundred percent metadata driven, integration definitions and rules can be activated in ETL (Extract, Transform, Load), EAI (transactions), SOA (Service-Oriented Architecture), and Data Virtualization. With the ease of configuring EE’s core data federation, data virtualization is part of any of these modes…

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Transformation-Federation Engine

At the core of Enterprise Enabler® (EE) is an engine that performs, in a single pass, data access from multiple disparate data sources, federation and alignment of the data across those sources, and virtualization or physical movement of the data…

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AppComm™ Technology

Connectivity to data is a fundamental requisite of any form of data or application integration. Every integration pattern relies on the ability to access data sources and destinations. Historically, integration platforms have pushed the responsibility out from the core of the pattern, usually by requiring data coming in and going out to be handed off in a specific, acceptable format…

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IaaS: Integration-as-a-Service

Integration of data across the enterprise has historically been anything but agile. Heavy architectures and complex integration tools have contributed to the ever-increasing ballast and IT’sinability to respond to the exploding volumes and new types of data. The IT department of many businesses have their hands tied…

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Real-Time Data Analytics

Data Analytics is becoming a key discipline for competitive advantage in many enterprises, and use cases for real-time analytics with Big Data are continuously surfacing with compelling value propositions. The legacy approaches to data preparation…

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