Data Fusion for ETL in GCP - Step-by-Step Execution

Process Flow - Data Fusion for ETL

Start Data Fusion Pipeline

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Extract Data from Source

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Transform Data

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Load Data to Destination

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Pipeline Completes Successfully

This flow shows how Data Fusion extracts data, transforms it, and loads it to the target system step-by-step.

Execution Sample

GCP

1. Create pipeline
2. Add source plugin
3. Add transform plugin
4. Add sink plugin
5. Run pipeline

This pipeline extracts data from a source, applies transformations, and loads it to a destination.

Process Table

Step	Action	Component	Data State	Result
1	Create pipeline	Pipeline	No data	Pipeline created and ready
2	Add source plugin	Source	No data	Source configured to read data
3	Add transform plugin	Transform	Raw data	Data transformation logic applied
4	Add sink plugin	Sink	Transformed data	Sink configured to write data
5	Run pipeline	Pipeline	Data flows	Data extracted, transformed, and loaded
6	Pipeline completes	Pipeline	Data loaded	Pipeline run successful

💡 Pipeline run completes after data is loaded to the destination

Status Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	After Step 5	Final
Data	None	Raw data extracted	Data transformed	Transformed data ready	Data loaded to sink	Pipeline complete

Key Moments - 2 Insights

Why does the data state change from 'Raw data' to 'Data transformed' at Step 3?

At Step 3, the transform plugin applies changes to the raw data, modifying it as per the pipeline logic, as shown in the execution_table row 3.

What happens if the sink plugin is not configured before running the pipeline?

Without the sink plugin configured (Step 4), the pipeline cannot load data to the destination, so the run at Step 5 would fail or not complete properly.

Visual Quiz - 3 Questions

Look at the execution_table, what is the data state after Step 3?

A Data transformed

B Raw data

C Data loaded

D No data

💡 Hint

Check the 'Data State' column for Step 3 in the execution_table.

At which step does the pipeline start running and data flows through components?

A Step 2

B Step 3

C Step 5

D Step 6

💡 Hint

Look for the 'Run pipeline' action in the execution_table.

If the transform plugin is removed, how would the data state after Step 4 change?

A Data would be loaded transformed

B Data would remain raw

C Data would be transformed

D No data would flow

💡 Hint

Refer to variable_tracker and execution_table rows for transform plugin effects.

Concept Snapshot

Data Fusion ETL pipeline:
1. Extract data from source
2. Transform data as needed
3. Load data to destination
Configure source, transform, sink plugins
Run pipeline to process data end-to-end

Full Transcript

Data Fusion for ETL involves creating a pipeline that extracts data from a source, applies transformations, and loads it to a destination. The pipeline is built by adding source, transform, and sink plugins. When the pipeline runs, data flows through these components step-by-step, changing state from raw to transformed to loaded. Proper configuration of each plugin is essential for successful execution.