For implementing a data analytics pipeline with real-time event streaming and batch processing, what combination of GCP services should be used for a robust, scalable, and cost-effective solution?

*The optimal combination of GCP services for building a robust, scalable, and cost-effective data analytics pipeline that includes real-time event streaming and batch processing is Pub/Sub for event streaming, Dataflow for transformation, and BigQuery for analytics. Pub/Sub provides a highly scalable and reliable platform for event ingestion, capable of handling high-volume real-time data streams. Dataflow seamlessly integrates with Pub/Sub and offers powerful data transformation capabilities, suitable for both stream and batch processing. BigQuery, as a highly performant and scalable data warehouse, is ideal for complex analytics and querying large datasets. This combination ensures a comprehensive solution covering all aspects of the pipeline, from data ingestion to processing and analytics. Other options like Bigtable, Firestore, or Data Catalog are not as well-suited for event streaming, and services like Dataprep and Cloud Functions may not offer the real-time processing capabilities required for such a pipeline.*