Section 3: Data Pipeline Orchestration - DEEPSEEK

Data Transformation Tools

Tools like Dataflow, Dataproc, Dataform, and Cloud Data Fusion for processing data.

ELT (Extract-Load-Transform)

Transforming data after loading it into the target system (e.g., BigQuery).

ETL (Extract-Transform-Load)

Transforming data before loading it into storage or analytics systems.

Cloud Composer

A managed Apache Airflow service for workflow orchestration in Google Cloud.

Dataproc

A service for running Apache Spark and Hadoop clusters for large-scale data processing.

Dataflow

A serverless tool for stream and batch data processing with autoscaling.

Dataform

A SQL-centric tool for building transformation pipelines in BigQuery.

Cloud Data Fusion

A GUI-based ETL/ELT pipeline builder with preconfigured connectors.

Data Orchestration

Coordinating automated workflows across data pipelines and services.

Cloud Scheduler

A cron job scheduler for triggering Google Cloud services at intervals.

Scheduled Queries

Automated execution of SQL queries in BigQuery (e.g., recurring reports).

Dataflow Job UI

A dashboard for monitoring pipeline progress, logs, and resource usage.

Cloud Logging

A centralized service for storing and analyzing logs from Google Cloud resources.

Cloud Monitoring

A tool for tracking performance metrics and setting alerts for pipelines.

Event-Driven Ingestion

Triggering data processing based on events (e.g., Pub/Sub messages).

Pub/Sub to BigQuery

Streaming data ingestion from Pub/Sub topics into BigQuery tables.

Eventarc

A service to route events from Google Cloud services to serverless functions.

Dataform Pipelines

Creating reusable SQL-based data transformation workflows.

Cloud Functions

Serverless functions triggered by events (e.g., file uploads to Cloud Storage).

Cloud Run

Serverless platform for running containerized applications in event-driven pipelines.

Dataproc Workflow Templates

Predefined workflows for recurring Spark or Hadoop jobs on Dataproc.

Workflows

A serverless orchestration tool for connecting Google Cloud services.

Pipeline Design

Planning data flow, dependencies, and tooling for efficient processing.

Basic Transformation Pipelines

Simple workflows for tasks like filtering, aggregating, or joining data.

Pipeline Automation

Using tools like Cloud Composer to reduce manual pipeline management.

Log Analysis

Using Cloud Logging to debug pipeline failures or performance issues.

Monitoring Metrics

Tracking pipeline health (e.g., latency, errors) via Cloud Monitoring.

Orchestration Tool Selection

Choosing between Cloud Composer, Workflows, or Dataproc based on use cases.

Eventarc Triggers

Linking events (e.g., Cloud Storage updates) to pipeline components like Dataflow.

Pipeline Progress Monitoring

Observing real-time status and metrics in the Dataflow job UI.