I wrote recently about SaaS construction collaboration technology vendors upgrading their hosting infrastructure, noting how 4Projects, Asite, Aconex and Conject had either already upgraded, or were in the process of upgrading their hosting facilities to keep ahead of the increased usage of their platforms. Implicit in many of the upgrades is an assumption that building information modelling (BIM) is placing increasing burdens on storage and data transfer bandwidth, and Conject‘s latest news release concerning an upgrade to its UK hosting makes this abundantly clear:
The pre-existing Conject infrastructure was robust, but the advent of BIM and the associated digitisation of information associated with the design, build and operation of a built asset means customers’ need for data storage is growing exponentially. In the last 12 months, three times more data has been uploaded to the Conject platform than in the corresponding period in 2011/2012, with BIM model files comprising 90% of this growth. The upgrade incorporates future-proofing of storage capacity.
Conject regional director Steve Cooper emphasises: “This upgrade means we will continue to provide very high levels of data security and maximise data availability well into the future,” while long-time client Mace Group’s Crawford Patterson says:
Conject’s investment in infrastructure means I can rely on the enhanced security and know we can access our information irrespective of the volume of data in our projects. My team also noticed an immediate improvement in overall system performance, particularly when running project queries and generating enterprise and programme level reports.
Conject UK’s latest blog post also provides an update on its progress regarding its BIM Common Data Environment (see my March 2015 post: Conject finally enters the BIM race), with senior product consultant Richard Moyle again stressing the key importance in BIM of “collaboration with control”. He adds: “More than 100 BIM projects are being supported by the Conject CDE, with varying levels of complexity”.