Google announced plans to make a big step forward with its Big Data solutions. In the official Google Cloud Platform Blog “big data, the cloud way” explains Product Manager William Vampenebe what it means exactly to use big data to the cloud type and how you have to think of data analysis using Google Cloud Platform:
Big data promises a better and faster insight into the company. However, it is often an infrastructure project. But why? For example, the fact that a flood of information collected must be linked and enriched in order to gain real-time insights. But one must now assume that such feats are naturally involves an enormous effort in terms of resource management and system administration? No way. Not in the cloud. Not when companies use big data to the cloud type.
Big Data to capitalize on the cloud type, means more productive when creating applications to be, namely the need to take care with faster and better insights and without worrying about the infrastructure. More specifically, this includes:
NoOps: The cloud provider should provide a scalable, reliable infrastructure, manage and update as needed. “NoOps” means that the platform these tasks and optimization decreases, so you can focus on the analysis and interpretation of the data fully.
Cost: The “NoOps” solution is not only user-friendly and flexible, it also offers clear cost advantages, since it saves operational processes. And Big Data in the cloud offers additional cost savings – scaled the platform and automatically optimizes the used infrastructure and makes unused resources like idle cluster superfluous. Costs can be controlled by individual cost-benefit considerations about the number of requests and the latency of the processes. There is no need to switch systems in order to optimize costs.
Secure and easy collaboration: files can be used in Google Cloud Storage or tables in BigQuery with employees within and outside your organization together without having to copy them or provide access to the database. There is always to control only one file and can be accessed only by authorized users, without incurring costs or the flow of processes is impaired.
Goggle has paved the way for Big Data, the entire industry – so if companies rely on Google Cloud Platform, then that is also to take advantage of big data to the cloud type using cutting-edge features. Google Cloud Dataflow enables by default the reliable processing of data in real time without the need for extra work would be necessary. But a simple and reliable data processing does not mean that there is no longer an option to perform batch processes.
The same process pipeline can also be run in batch mode, use the company to reduce costs or to analyze historical data. The consistent processing of large amounts of data is now not a complex, arduous task more that one takes in very critical situations in coming. With Google Cloud Platform data analysis is fast, inexpensive and easy to do.
With HP Service Anywhere HP announces a service desk solution for IT service management (ITSM) in order to help companies to fix faults in the IT quickly.
The new ITSM solution is marketed as a software-as-a-Service (SaaS) and is easy to implement in this way, to use and update. In addition, HP offers an HP Service Anywhere Foundation Service that allows customers the service desk solutions quickly introduce and integrate into their IT environment a quick start service.