What's changed: Created Cloud Digital Leader Chapter 2 (Domain 2 "Data": value and types of data = structured/semi-structured/unstructured, batch/streaming; Google Cloud data management = Cloud Storage/Cloud SQL/Spanner/Firestore/Bigtable/BigQuery/Dataflow/Pub/Sub/Looker).
2.2Google Cloud data management solutions
Understand the roles and selection of Google Cloud’s key data services: relational databases (Cloud SQL, Spanner), NoSQL (Firestore, Bigtable), object storage (Cloud Storage), data warehouse (BigQuery), data pipelines (Dataflow, Pub/Sub), and business intelligence (Looker).
Google Cloud offers purpose-built managed services for each data type and use case. Cloud Digital Leader asks you to map "which service for which use case." Here are the key services organized by role.
2.2.1Databases and storage
| Service | Kind | Typical use |
|---|---|---|
| Cloud Storage | Object storage | Images, video, backups, unstructured data |
| Cloud SQL | Managed relational DB | MySQL/PostgreSQL/SQL Server-compatible apps |
| Spanner | Global distributed relational DB | Global, strongly consistent, high-availability core systems |
| Firestore | Document NoSQL | Mobile/web app data |
| Bigtable | Wide-column NoSQL | IoT, time series, huge-scale data |
Cloud Storage is object storage for unstructured data like images, video, and backups. Cloud SQL is a managed relational DB compatible with MySQL/PostgreSQL/SQL Server for typical business apps. Spanner is a distributed relational DB combining global strong consistency and high availability for global core systems. For NoSQL, Firestore suits mobile/web apps, while Bigtable suits huge-scale, low-latency workloads like IoT and time series.
Cloud Storage offers storage classes that lower cost by access frequency. Use Standard for frequently used data, Nearline for roughly monthly access, Coldline for roughly quarterly access, and Archive for long-term, rarely read data. Less-accessed classes have lower storage cost but higher retrieval cost. The principle is "the less often you use it, the cheaper the class," and lifecycle management can move data automatically. To use data with confidence, data governance (who can access which data, and how quality and regulations are upheld) is essential and forms the foundation of data utilization.
2.2.2Analytics and pipelines
BigQuery is Google Cloud’s flagship serverless data warehouse, analyzing petabyte-scale data quickly with SQL and integrating with AI (BigQuery ML). To move data between services, use Dataflow (batch/streaming data-processing pipelines) and Pub/Sub (real-time messaging). To visualize results for the business, build dashboards with Looker (business intelligence). Remember the roles as a flow: "store → move → analyze → visualize."
Common: use case → service. E.g., "petabyte-scale SQL analytics warehouse" = BigQuery; "store images/video/backups" = Cloud Storage; "MySQL/PostgreSQL-compatible business DB" = Cloud SQL; "global strongly consistent core DB" = Spanner; "huge-scale IoT data" = Bigtable; "real-time message ingestion" = Pub/Sub; "data-processing pipeline" = Dataflow; "BI dashboards" = Looker.
Watch the mix-ups: (1) BigQuery (analytics = data warehouse) vs Cloud SQL/Spanner (transactions = business DBs) differ in role. (2) Cloud Storage is object storage, not a file system or DB. (3) Keep Pub/Sub (messaging) and Dataflow (processing pipeline) distinct. (4) Spanner (global strong consistency) vs Cloud SQL (single/regional business DB) differ in scale.
2.2.3Section summary
- DB/storage = Cloud Storage (unstructured) / Cloud SQL (relational) / Spanner (global strong consistency) / Firestore, Bigtable (NoSQL)
- Analytics = BigQuery (serverless DWH); pipelines = Dataflow + Pub/Sub; visualization = Looker (BI)
- Organize roles as "store → move → analyze → visualize" and pick by use case
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Quick check
(just a quick review)Q1. Which is Google Cloud’s serverless data warehouse for fast SQL analytics at petabyte scale?
Q2. Which Google Cloud service best stores unstructured data such as images, video, and backups?
Q3. Which suits a business app needing a managed relational database compatible with MySQL or PostgreSQL?
Q4. Which relational database provides global strong consistency and high availability for core systems?
Q5. Which messaging service ingests messages in real time and delivers them between services?
Q6. Which business intelligence service visualizes results in dashboards to support business use?