The Importance Of Edge Computing In Industrial Transformation

Self-service Analytics BI is often quoted by many - ie, allow users to discover and access data without having to ask IT to create a data mart, or by allowing users to directly export/copy the data from the data sources themselves into their analytics tools and systems. The challenge is not just to provide access to the data – even from Excel this can be done - but to do this in real time without creating processing overhead, while getting trusted data, with the best response time possible, in a managed, governed and secure way in order for these users to trust the output of the analysis. Data Virtualization provides a data access platform that allows users to access the data they need from multiple data sources, when they need it, and with the best possible response time. In addition, a Data Marketplace built on top of this proven technology enables Self Service Analytics by exposing consistent and governed data sets to be discovered by users, providing the trusted foundation for a successful Self-Service Analytics initiative.

Data lakes have grown to be a popular architecture that enables modern analytics and data science. However, complete replication of all corporate data into giant data lakes is unfeasible. Data volumes are too high, and replication to multiple systems creates brittle point-to-point connections. Out-of-synch data and uncontrolled replication leads to “data swamp” scenarios. On top of the physical data lake, a logical approach is more feasible: a logical layer that connects different systems.

Whether you’ve recently virtualized or you’re newly responsible for your virtualization environment, you may have found your new world to be complicated. So where do you start when it comes to troubleshooting? And where should you focus if you want to reclaim resources and find some savings? This webinar will share some practical, actionable advice on how to understand the current state of your systems, how to troubleshoot faster when issues come up, and where to look when it’s time to optimize. We’ll also show you how to visualize virtualization in the context of the rest of your IT infrastructure.

While VMware workloads can now run natively on Google Cloud, they still require a rich set of data management tools. Cloud Volumes ONTAP equips you with everything you’ll need. Watch our webinar to learn how Cloud Volumes ONTAP and Google Cloud VMware Engine come together.