The decentralization of eDiscovery workforces engaged in tasks ranging from on-site collections to remote reviews coupled with the desire of organizations to reduce investments in IT infrastructure and hardware is causing data and legal discovery leaders to carefully consider virtual desktop infrastructure (VDI) and Desktop-as-a-Service (DaaS) approaches for delivering access to eDiscovery applications needed to support audit, investigation and litigation projects and programs. The following two articles highlight VDI and DaaS and share considerations that may be useful for individuals interested in understanding and evaluating VDI and DaaS in support of eDiscovery.
Epiq announces the release of its new cloud-based eDiscovery platform, Epiq Discovery. Epiq Discovery is a collection, processing, review, and production platform that delivers early case assessment, highly scalable processing, and the most efficient review and production of eDiscovery data.
“To meet developers’ needs, we looked at multiple different approaches to supporting MongoDB workloads and concluded that the best way to improve the customer experience was to build a new purpose-built document database from the ground up, while supporting the same MongoDB APIs that our customers currently use and like. This effort took more than two years of development, and we’re excited to make this available to our customers today.”
Price transparency is going out of fashion among SaaS vendors as many say ‘Call for pricing’. Vijay Sundaram explains why that’s a bad thing. Put simply, customers need more information, not less, about business software in order to make informed decisions.
To help companies embrace the hybrid cloud, Amazon Web Services recently announced plans to provide enterprises with on-premises hardware that will allow them to use AWS cloud services inside their own data centers.
ERP vendors and pure-play SaaS vendors are genetically and fundamentally different. While the former like to tell us they’re now a SaaS business, most aren’t. Just as tigers can’t change their stripes, old-line ERP vendors don’t become real SaaS firms just because they say they are.
Revenue from licensed products, such as traditional software run on a customer’s own servers and computers, is now recognized upfront.
In this extract from the article “15+ of The Top Sales & Marketing Mistakes SaaS Startups Make,” Jason Lemkin highlights major mistakes in marketing that may inhibit SaaS success.
By and large, the most frequent applications of machine learning in SaaS today are efficiency applications – automating the high-volume rote processes and reducing costs.
There are hundreds of different metrics that product managers could potentially measure. But all successful teams have a core set of metrics that matter most to them and the nature of their business.