Data Insights & Analytics — CDL Study Guide

Unlock the complete study guide + 1,040 practice questions across 16 full exams.

Bundled into the existing Cloud Digital Leader premium course — no separate purchase.

Included in this chapter:

From stored data to a business decision
Looker: self-service BI on a governed semantic layer
Real-time value: batch vs streaming analytics
The streaming pipeline: Pub/Sub and Dataflow

Roles in a Google Cloud data-to-insight pipeline

Product	Stage	What it does	Managed/serverless?
Pub/Sub	Ingest	Receives and buffers real-time event streams; decouples publishers from subscribers	Yes
Dataflow	Process / transform	Cleans, enriches, and aggregates data in stream or batch	Yes
BigQuery	Store / analyze	Serverless data warehouse that runs SQL analytics at scale	Yes
Looker	Visualize / explore	Self-service BI with a governed metric layer; queries BigQuery live	Yes

Cheat sheet

Cheat sheet

Stored data creates no value until it is analyzed and visualized
Looker is Google Cloud's business intelligence and visualization platform
Looker democratizes data through self-service exploration
LookML defines each metric once as a single source of truth
Looker queries the warehouse live instead of copying data out
BigQuery is the analytics engine; Looker is the layer on top
Looker can embed analytics inside other applications
Batch processes data in scheduled groups; streaming processes it as it arrives
Choose streaming analytics when decisions cannot wait for the next batch
Pub/Sub is the serverless ingestion front door for event streams
Pub/Sub decouples publishers from subscribers asynchronously
Dataflow is the serverless engine that processes and transforms the data
Dataflow handles both streaming and batch with one model
Pub/Sub and Dataflow are the paired data-pipeline products
The streaming pipeline flows ingest to process to store to visualize

Unlock with Premium — includes all practice exams and the complete study guide.

Also tested in

PDE Professional Data Engineer

References