Data Streams and Approximation

This lecture covers the management of data streams, contrasting traditional DBMS with distributed, continuous, and unbounded data streams. It explores real-time network analytics applications, such as stock monitoring and IP traffic analysis. The lecture also delves into the challenges of processing data streams in real-time and the differences between databases and data streams. Additionally, it introduces the data stream model, discussing the underlying signal representation, stream of updates, and special cases like the cash-register, turnstile, and time-series models. The lecture concludes by examining the facets of data and time in data stream processing, including solutions for handling large volumes of data and defining query ranges.