Internet of Things (IOT) | Vast Edge Analytics Solutions

Data Analytics  Cloud Integration  Mobile Security   Business Process as a Service

Internet of Things (IoT) has become a pragmatic approach for the development of Internet in a way that it includes all those objects which are capable of exchanging digital data to establish wired and wireless network connectivity. The data produced from IoT can prove as a great asset for the companies to capture deep insights of customer intelligence and enhance the operational efficiency of risk analytics tools.

Unlock IoT Opportunities with Analytics for Business Success

Using the potential of cloud computing technologies, businesses can modernize their existing infrastructure and deliver high-speed application services to their customers. The cloud represents a shining spot and a huge platform with enormous opportunities for IoT initiatives to easily adapt and transform their technology into a hybrid IT service environments. Bringing IoT to the multitude of technology services, Cloud-enabled computing capabilities enhance the potential of business organizations to grow in the market with a competitive advantage.
Companies that deploy cloud-based service models to run their business applications and deliver their services to the masses are more likely to gain instant access to long-term historical intellectual data assets of their businesses.However, to monetize this opportunity and integrate data-driven business models using the power of the cloud, SMBs and large organizations require a platform to generate connected business intelligence.

IoT Holds Tremendous Potential for Businesses in Future

To harness the power of IoT and Cloud Analytics together so as to produce effective results, it is necessitated to have a deep understanding of the involved process for extracting the meaningful information from the IoT data. This data if used to good advantage can stimulate effective improvements in a broad category of data-driven business processes.The opportunity of IoT if exploited properly and put to work in an advantageous manner can raise the percentage increase in RoI of the business and aid in better customer experience.
There is no denying the fact that IoT is the need of the hour and this future of technology can shape our lives more efficiently if put to work in a scalable manner.This can be achieved by acquiring and analyzing the data received from various IoT devices or sensors and process the data operations in a cost effective manner.

VastEdge Cloud Analytics Solutions for IoT

The Internet of Things is the concept that finds its space in every walk of life from industrial machines to sensors and wearable devices. Gathering the data and taking action on that data in real time across a network is the beauty of IoT analytics. Thus, there exists a need for utilizing big data platforms that can fetch and streamline real-time data integration for both IT and business operations simultaneously. Vast Edge is a certified partner of global technology leaders like SAS, IBM, Microsoft, AWS, Cisco, and Oracle and provides services for IoT with cloud analytics.

SAS

SAS Analytics for IoT empowers analysts and programmers in various organizations to commence the execution of their IoT use cases. Supported by SAS Event Stream Processing Studio and SAS® LASR Analytic Server, it facilitates edge analytics for building applications using the C++ Modeling API or the XML Modeling Layer. Additionally, it provides faster, secure, and multi-user access to in-memory data.

IBM

IBM Bluemix is a fully managed, cloud-hosted service that simplifies extracting value from various IoT devices. It also facilitates the transformation of your business using Watson IoT in a scalable manner, incorporating APIs and other software services

Microsoft

With Microsoft Azure IoT Suite, businesses can expedite their IoT projects by leveraging pre-configured analytics solutions, gaining a competitive edge in the market. This open, flexible solution allows you to capture insights from data using machine learning and predictive modeling techniques.

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