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Building streaming data pipelines on Google Cloud Streaming analytics pipelines are designed to process and analyze real-time data streams, allowing organizations to derive insights and take immediate actions. The architecture of streaming analytics pipelines can vary based on specific use cases, requirements, and the technologies chosen. However, a typical streaming analytics pipeline consists of several key components. Here's a general overview: 1. Data Sources: Streaming Data Generators: These are the sources that produce real-time data streams. Examples include it devices, social media feeds, log files, sensors, and more. Google Cloud Data Engineer Training 2. Data Ingestion: Ingestion Layer: Responsible for collecting and bringing in data from various sources. Common tools and frameworks include Apache Kafka, Apache Flank, Apache Pulsar, Amazon Kinesis, and more . GCP Da...