Quick cloud adoption is one of primary factors of success in modern digital business. Microsoft Office 365 and SharePoint Online play notable role in this increasing bias towards cloud business platforms. To facilitate and streamline cloud transformation scenarios we created Enterprise Bridge, revolutionary product, which fully automates complex content deployment scenarios in modern hybrid clouds.
Enterprise Bridge to SharePoint promotes transparency in Microsoft cloud environments through seamless incremental integration of local resources, on premise servers and contemporary cloud platforms. Configurable transformation workflows allow for selective mapping of data and metadata across all supported platforms, retains original associations of users, groups and access rights across the migrated content.
This unique range of elaborate technology, flexibility, convenience and simplicity explains growing popularity of this solution. High user ratings were proven in "Rising Star" and "Great User Experience" award given to Enterprise Bridge by the expert team of FinanceOnline in their recent review: https://reviews.financesonline.com/p/enterprise-bridge-to-sharepoint/
Join companies who already use Enterprise Bridge as the reliable basis for quick cloud deployment strategy and stay abreast of competition in winning efficiency and excellence of your digital transformation.
There always exists a discrepancy between a model of business process, however well designed and accurate, and real execution of this process in a business environment. The reason for this gap is an unforeseen depth and hidden details inherent to any real process. Real business model of organization is ultimately unlimited in its depth. Going from highest management levels, it descends to individual departments, client relations, production units, technical code of equipment and controllers etc. In vast majority of cases, it is impossible and senseless to build a complete model covering all and every fine detail of the business. Omitted lower layers of the model create (pseudo) random fluctuations during execution of the model. Real execution paths of a process never follow its model exactly. However, in case of the correct model, we can expect to see that an ensemble of execution paths statistically converges to the model as to its average path over a significant set of observation...
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