Network Analytics (VISTA)
Discovering New Insights
with Samsung VISTA
Samsung VISTA is a suite of analytics tools that collects and monitors data to analyze traffic, service and user patterns and utilize such findings to enhance network performance and subscriber service quality satisfaction. By combining AI-based analytics and automation, Samsung is enabling operators to increase network operational efficiency, reduce OPEX and improve the quality of experience.
VISTA leverages AI-driven holistic subscriber management by
collecting and unifying and encompassing Performance Management, Fault Management, Service Quality Management and Customer Experience Management into a holistic umbrella able to provide end-to- end Customer Experience aided by the latest advances in Artificial Intelligence and Machine Learning.
Highly scalable Massively Parallel Processing platform.
VISTA components may be distributed throughout multiple machines and locations in order to get the most of all the hardware and take advantage of important data characteristics as locality. Inside VISTA, here are two elements of paramount importance:
Schema-less columnar store.
Big Data schema-less distributed columnar store used for storing data and correlate it in near real- time.
Streaming Dataflow engine.
This engine is responsible for parallelizing the different tasks and make them run using all the available hardware resources.
Thanks to the openness of VISTA, several out-of- the box applications packages are provided to cover different needs in Operators (e.g. customer experience, network intelligence, customer intelligence, Trace Analytics, data exporting, network monitoring, etc).
This makes the VISTA product suite unique in its approach as it covers all the process from the collection to the analytics and actuation processes.
Ready to work with 3 rd -party applications by using different Hadoop, Spark or REST API interfaces.
Big data architecture
Leveraging distributed file system, columnar
stores and execution paradigms.
Built-in AI-Powered Use Cases and ML Models to enable network automation and actuation.
Running on public (AWS, Google Cloud, Azure, etc.), private and hybrid clouds.
Cross-domain, integrating RAN, Core, IMS, OSS and BSS data sources under a common platform.