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Google Cloud for data — BigQuery, Dataflow, Pub/Sub, Vertex AI, Cloud Storage and the Professional Data Engineer path.
GCP articles
Loading Data into BigQuery: Batch and Streaming
BigQuery can be loaded in batches from files or fed continuously through the Storage Write API. This guide compares the methods by latency, cost, limits and what a retry does, with documented commands, a model of at-least-once against exactly-once delivery, and a rule for choosing.
Looker and Looker Studio on GCP Explained
Google has two BI tools with similar names and different jobs. Data Studio, the new name for Looker Studio, builds self-service reports at no cost. Looker adds a central model that defines each metric once. This guide compares them and uses a real database to show the mistake a shared model prevents.
GCP Professional Data Engineer Certification Guide
The Professional Data Engineer exam tests design judgement more than commands. This guide sets out the facts from Google's exam page, the five sections and their weights, a table matching the product names in the exam guide to the names in today's documentation, and a way to prepare by building.
Materialized Views in BigQuery Explained
A materialized view stores the result of a query and keeps it current as the base table changes. This guide shows how BigQuery combines stored results with new rows, models it on 2.9 million real trips, and covers refresh settings, max_staleness, smart tuning, unsupported SQL and when a scheduled table is better.
Migrating to BigQuery: A Practical Playbook
Moving a warehouse to BigQuery is less a copy job than a proof: that the SQL still means the same thing and the numbers still match. This playbook follows Google's iterative method, then reproduces two steps locally: a translator that gets one statement wrong, and a copy that passes row counts while 23 rows differ.
Scheduling Queries in BigQuery
A scheduled query is SQL that BigQuery runs for you on a timetable. This guide covers the run parameters, destination table templates checked against Google's own examples, backfills, credentials and notifications, and shows on real data why an appending statement doubles on a rerun while a MERGE does not.