Google Cloud Professional Data Engineer | Ingest & Process Data Part 1: Core Exam Scenarios

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This video focuses on the Ingest & Process Data domain of the Google Cloud Professional Data Engineer exam. Learn how to choose the right ingestion and processing solutions for batch and streaming pipelines using Pub/Sub, Dataflow, Dataproc, and more. All examples are aligned with real exam-level decision making.
TIMESTAMP
0:00 - Disclaimer
0:14 - Session Format
0:35 - What to Expect
0:44 - Exam + Domain Scope

0:55 - Q1 – Exactly-once global clickstream processing
1:23 - Q2 – Ordered financial trading ingestion design
1:51 - Q3 – Auto-scaling IoT ingestion pipeline
2:19 - Q4 – Unified batch and streaming processing logic
2:47 - Q5 – Hourly file ingestion with heavy transforms
3:15 - Q6 – Preventing duplicate BigQuery streaming writes
3:43 - Q7 – High-throughput BigQuery bulk ingestion
4:11 - Q8 – Regional healthcare streaming compliance
4:39 - Q9 – Mitigating skew in streaming pipelines
5:07 - Q10 – Durable messaging during downstream outages
5:35 - Q11 – Low-overhead hybrid ingestion from on-prem
6:03 - Q12 – Streaming enrichment with daily reference data
6:31 - Q13 – Default delivery guarantee semantics
6:59 - Q14 – Stabilizing long-running batch workloads
7:27 - Q15 – Near-real-time analytics ingestion choice
7:55 - Q16 – JSON schema evolution handling
8:23 - Q17 – Exactly-once BigQuery streaming guarantees
8:51 - Q18 – SQL-based serverless stream transformations
9:19 - Q19 – Durable raw data landing storage
9:47 - Q20 – Handling late-arriving streaming events
10:15 - Q21 – Historical message replay strategy
10:43 - Q22 – Large-scale transformation join architecture
11:11 - Q23 – Cost-efficient scheduled batch compute
11:39 - Q24 – Schema enforcement during ingestion
12:10 - Q25 – Ultra-low latency streaming processing

12:38 - Playlist + PDF Access

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