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Google Cloud for data — BigQuery, Dataflow, Pub/Sub, Vertex AI, Cloud Storage and the Professional Data Engineer path.
GCP articles
Cloud SQL vs Spanner vs Bigtable: When to Use Each
Cloud SQL is a managed MySQL, PostgreSQL or SQL Server. Spanner is a relational database that scales across regions with strong consistency. Bigtable is a wide-column store for huge volumes read by key. This guide compares them, models on real data why a Bigtable row key decides everything, and gives a way to choose.
GCP Free Tier: What You Can Build Without Paying
Google Cloud has three free offers, and they are often confused: the BigQuery sandbox, the 90-day Free Trial and the permanent Free Tier. This guide separates them, lists the limits that matter for data work, checks a learner's pipeline plan against those limits, and names the services that are not covered.
Data Catalog and Governance on GCP
Data Catalog has been retired and its role has moved to Knowledge Catalog, the new name for Dataplex Universal Catalog. This guide explains what a catalogue holds, how entries, aspects and glossaries work, what lineage and quality scans add, and derives lineage from four SQL statements to show impact analysis.
BigQuery ML: Machine Learning with SQL
BigQuery ML trains and runs machine learning models with SQL, on data that never leaves the warehouse. This guide covers the statements, model types and pricing, then reproduces a logistic regression locally on 300,000 real trips to show what the evaluation numbers mean and three ways an easy model can mislead.
GCP Associate Cloud Engineer Certification Guide
The Associate Cloud Engineer exam checks whether you can set up, run and secure things on Google Cloud. This guide gives the facts from Google's exam page and exam guide, including the four sections and their weights, says what the certificate does and does not show, and sets out a hands-on study plan.
GCP vs AWS vs Azure for Data Engineering
The three large clouds solve the data engineering problem with the same building blocks under different names. This comparison maps the services layer by layer using the vendors' own tables, shows where those tables disagree, writes one file load for BigQuery, Redshift and Synapse, and gives plain rules for choosing.