To establish a comprehensive data lake solution in GCP that handles batch and stream data ingestion, as well as transformations and analytics with SQL-like queries, which set of GCP services should be utilized?
- BigQuery, Cloud Pub/Sub, and Dataflow
- BigTable and Dataprep
- BigQuery and Dataprep
- Cloud Spanner, Dataflow, and BigQuery
- Cloud Storage, BigQuery, and Cloud Scheduler
Explanation:
The combination of BigQuery, Cloud Pub/Sub, and Dataflow is the most suitable for building a robust data lake solution in GCP. BigQuery is a powerful data warehouse that supports SQL-like queries, making it ideal for analytics. Cloud Pub/Sub facilitates real-time data ingestion, which is crucial for handling stream data. Dataflow, on the other hand, provides a platform for both batch and stream data processing and transformations. This trio of services works together seamlessly to offer a comprehensive solution that covers all aspects of a data lake, including data ingestion, processing, and analysis. The other combinations, while having their own strengths, fall short in providing a complete solution that encompasses all these capabilities.