Modern Trends in Analytics and the Internet of Things
Modern implementations of the Internet of Things (IoT) have significantly changed technological processes, moving beyond industrial automation. Thanks to technology advancements, users have gained new cloud services and analytical tools. Previously, software for managing technological processes was complex to use and costly. Today, this situation is changing. With a variety of applications for IoT, cloud platforms with advanced development environments allow for the creation and customization of analytics, reducing the costs of implementation. This can be compared to the popularity of Excel spreadsheets, which help users utilize computers more efficiently.
With enhanced analytics, decision-making processes can be significantly improved, leading to the optimization of production processes. Examples of such new offerings include Google Analytics and Measurement Protocol, Microsoft Azure machine learning, and AWS IoT (Amazon Web Services IoT).
Cost-effective Solutions for Data Archiving
Data archiving servers have already proven their effectiveness in technological processes, but their use in discrete applications was previously hindered by high initial deployment and maintenance costs throughout their lifecycle. However, with the emergence of commercial cloud services, many companies find it economically advantageous to use data archives and analytics in necessary locations.
Many large users collecting data from factories using OPC technology, OPC UA, and other gateways transfer data to popular cloud services from providers such as Amazon Web Services (AWS) and Microsoft Azure. This approach demonstrates its effectiveness and flexibility, allowing companies to maximize their analytical capabilities.