Identify different batch and streaming data sources

Activity overview
Timely access to data is critical for organizations to respond quickly to market changes, customer needs, and operational issues.

Batch processing is a method of collecting large volumes of data over a period of time, then processing it all at once. It is best for processing large amounts of data and tasks that do not require near real-time processing.

Streaming processing is a method of processing data as it is received. It is best for processing data continuously in real time. It is important for data analysts and data scientists to understand the difference between the two since both processes have their own advantages and disadvantages.

As a data analyst, knowing when and how to apply batch processing or streaming processing helps you optimize the performance of data processing tasks, minimize time delay in data processing, and provide more accurate and timely data insights.

In this lab, you’ll process and collect data for a specific purpose, and observe the data loading in BigQuery tables using both computer-assisted batch processing and stream processing methods.
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