What is the primary objective of analyzing time-stamped data with Time Series Insights?

The primary objective of analyzing time-stamped data with Time Series Insights is to gain actionable insights. Time Series Insights is designed to allow users to understand trends, patterns, and anomalies in their time-stamped data, particularly in the context of IoT applications. By analyzing this data, organizations can derive meaningful conclusions that enable them to make informed decisions, optimize operations, and enhance performance across their devices and systems.

While storing historical data is essential, it is not the main goal of Time Series Insights. Similarly, visualizing sensor data is a means to facilitate the analysis but does not represent the ultimate aim—which is to understand and extract value from that data. Tracking device performance can indeed be a part of the insights derived, but the broader objective encompasses all aspects of gaining actionable insights from the analysis of time-stamped data. Therefore, the focus on actionable insights highlights the comprehensive role of Time Series Insights in transforming raw data into valuable business intelligence.