Harnessing Composite Variables for Real-Time Data Analysis

Telit Cinterion · Intermediate ·📊 Data Analytics & Business Intelligence ·1y ago
Skills: BI Tools53%

About this lesson

Watch this webinar to gain a better understanding of composite variables and how to use them for real-time data analysis. Take your solutions to the next level with data orchestration. Request a consultation: https://www.telit.com/iot-consultation/ Data utilization has significantly changed. Before, data was mainly used to automate individual tasks. The focus has moved to analyzing data in real time so that companies can improve performance and efficiency. These capabilities empower them with more accurate forecasts and greater flexibility. This movement has meant that businesses need advanced data analytics tools to handle complicated information. One approach uses composite variables, which combine two or more scalar variables (i.e., single data points). One example is overall equipment effectiveness (OEE). OEE is calculated by multiplying: • Availability rate • Performance rate • Quality rate These composite variables offer great benefits for data analysis and AI applications. Join us for a webinar as we discuss composite variables and their role in data analysis. You will see how they serve as the basis of data that AI systems and analysis tools in cloud platforms can use. In this session, we will explore the practical applications of composite variables to improve data-driven decision-making. You will learn how these variables are changing data analysis across multiple industries and how to implement them with the deviceWISE® platform, powered by Telit Cinterion. Attendees will learn: • The differences between composite and scalar variables to understand them better • The benefits of leveraging composite variables for analyzing data • The advantages of a comprehensive IoT systems management platform • How to provide next-level solutions by orchestrating machine data • How deviceWISE uses its built-in unified namespace and PeerLink features to analyze and access industrial data ▶ IoT Central: A Guide to Measuring Overall Equipment

Original Description

Watch this webinar to gain a better understanding of composite variables and how to use them for real-time data analysis. Take your solutions to the next level with data orchestration. Request a consultation: https://www.telit.com/iot-consultation/ Data utilization has significantly changed. Before, data was mainly used to automate individual tasks. The focus has moved to analyzing data in real time so that companies can improve performance and efficiency. These capabilities empower them with more accurate forecasts and greater flexibility. This movement has meant that businesses need advanced data analytics tools to handle complicated information. One approach uses composite variables, which combine two or more scalar variables (i.e., single data points). One example is overall equipment effectiveness (OEE). OEE is calculated by multiplying: • Availability rate • Performance rate • Quality rate These composite variables offer great benefits for data analysis and AI applications. Join us for a webinar as we discuss composite variables and their role in data analysis. You will see how they serve as the basis of data that AI systems and analysis tools in cloud platforms can use. In this session, we will explore the practical applications of composite variables to improve data-driven decision-making. You will learn how these variables are changing data analysis across multiple industries and how to implement them with the deviceWISE® platform, powered by Telit Cinterion. Attendees will learn: • The differences between composite and scalar variables to understand them better • The benefits of leveraging composite variables for analyzing data • The advantages of a comprehensive IoT systems management platform • How to provide next-level solutions by orchestrating machine data • How deviceWISE uses its built-in unified namespace and PeerLink features to analyze and access industrial data ▶ IoT Central: A Guide to Measuring Overall Equipment
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