Streaming data records are typically small, measured in mere kilobytes, but the stream often goes on and on without ever stopping. Streaming data, also called event stream processing, is usually ...

Reduced Cost: Data streaming for business is already processed and analysed, they do not have to invest in warehousing or storage of data. Along with this, the costing for analysis is saved too. Also, ...

Unlocking the true promise of streaming data and maximizing your enterprise’s streaming intelligence is only possible with the right technologies in place.

Spark Streaming ecosystem: Spark Streaming can consume static and streaming data from various sources, process data using Spark SQL and DataFrames, apply machine learning techniques from MLlib, and ...

Streaming data — also called real-time data — is information that arrives continuously from various sources and is analyzed quickly so businesses can respond in near-real time to events on the ...

Streaming data analytics, when performed with data generated continuously by multiple sources, is a powerful tool for understanding conditions in constant change.

Today we know that data flows to such an extent that we now talk about data streaming, but what is it and how do we harness this computing principle?