Data Fusion for ETL in GCP - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is Google Cloud Data Fusion?

Google Cloud Data Fusion is a fully managed, cloud-native data integration service that helps you build and manage ETL (Extract, Transform, Load) pipelines visually without writing code.

beginner

What does ETL stand for in Data Fusion?

ETL stands for Extract, Transform, Load. It means taking data from sources, changing it to the needed format, and loading it into a destination for analysis or storage.

intermediate

How does Data Fusion simplify building ETL pipelines?

Data Fusion provides a drag-and-drop interface with pre-built connectors and transformations, so you can visually design pipelines without coding, making it easier and faster to prepare data.

beginner

What is a pipeline in Data Fusion?

A pipeline is a sequence of steps that extracts data from sources, transforms it, and loads it into targets. In Data Fusion, pipelines are visual workflows that automate data processing.

beginner

Name two common data sources you can connect to with Data Fusion.

You can connect to sources like Google Cloud Storage and BigQuery, among many others, to extract data for your ETL pipelines.

What is the main purpose of Google Cloud Data Fusion?

A To build and manage ETL pipelines visually

B To store large amounts of data

C To run virtual machines

D To create machine learning models

Data Fusion is designed to help users build ETL pipelines visually without coding.

In ETL, what does the 'Transform' step do?

A Extracts data from sources

B Changes data into the needed format

C Loads data into the destination

D Deletes old data

The 'Transform' step modifies data to fit the target format or requirements.

Which interface does Data Fusion use to build pipelines?

A Spreadsheet

B Command line only

C Text editor

D Drag-and-drop visual interface

Data Fusion provides a drag-and-drop interface for easy pipeline creation.

Which of these is NOT a typical Data Fusion pipeline step?

A Compile

B Transform

C Load

D Extract

'Compile' is not part of ETL steps; ETL includes Extract, Transform, and Load.

Which Google Cloud service is commonly used as a data source in Data Fusion?

A App Engine

B Compute Engine

C BigQuery

D Cloud Functions

BigQuery is a common data warehouse used as a source or target in Data Fusion pipelines.

Explain how Google Cloud Data Fusion helps in building ETL pipelines.

Think about how it makes ETL easier for people who don't want to write code.

Describe the three main steps of ETL and their roles in data processing.

ETL is like preparing ingredients, cooking, and serving a meal.