Digital Business Platform for Machine Learning Apps: Data Feedback Loops
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Big data pros need to identify which data feedback loops in their machine learning applications can deliver sustainable differentiation through network effects. Starting early is critical because getting to scale is likely to create the “winner takes most” competitive dynamics that have become so common in tech industries. The biggest sin is to wait for the tooling to become automated enough for all competitors to jump in.
1H2016 Public Cloud Market Share Report Update
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The public cloud competitive environment remains turbulent, but sectors show signs of crystallizing a longer-term market structure.. SaaS remains turbulent with SaaS vendors successfully gaining share vs. incumbent licensed software providers who must migrate their core products to cloud-friendly offerings and/or acquire native SaaS applications to shore up their applications leadership positions. Public cloud IaaS segment leadership is crystallizing to a handful of viable providers as a function of scale requirements. PaaS is just formulating and finding its way, but is likely to gravitate towards a wide variety of development models suited for different application types and public cloud platforms.
Real-time Recovery Architecture as a Service
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For enterprise executives trying to achieve aggressive RPO and RTO SLAs , Wikibon believes that batch backup appliances (PBBAs) will give way to real-time, continuous data protection systems that aggressively support very large memory application memory. Practitioners requiring close to RPO zero and aggressive RTO SLAs should plan for an integrated data protection approach that effectively eliminates the concept of storage-led backup and shifts thinking to a application-led virtual point-in-time recovery model. The database and file system vendors will be the predominant suppliers of this technology, and understanding their roadmaps and commitment to support application-led recovery strategies is crucial to both database and data protection technology selection.