# cloud dataproc

Published articles for cloud dataproc.

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## Implementing ETL on GCP

DevFeed: [Implementing ETL on GCP](<https://devfeed.tech/articles/implementing-etl-on-gcp-22998.md>)

Original publisher: [Read original article](<https://bravenewgeek.com/implementing-etl-on-gcp/>)

Author: Deepmala

Published: 2020-07-15T20:53:17Z

Content type: tutorial

Language: en

Sources: [Brave New Geek](<https://devfeed.tech/sources/brave-new-geek.md>)

Topics: [DataOps](<https://devfeed.tech/topics/dataops.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [BigQuery](<https://devfeed.tech/topics/bigquery.md>), [data loss prevention](<https://devfeed.tech/topics/data-loss-prevention.md>), [Low code](<https://devfeed.tech/topics/low-code.md>), [No-code](<https://devfeed.tech/topics/no-code.md>), [olap](<https://devfeed.tech/topics/olap.md>)

Tags: [analytics](<https://devfeed.tech/tags/analytics.md>), [analytics-pipeline](<https://devfeed.tech/tags/analytics-pipeline.md>), [bi-tools](<https://devfeed.tech/tags/bi-tools.md>), [bigquery](<https://devfeed.tech/tags/bigquery.md>), [cdap](<https://devfeed.tech/tags/cdap.md>), [cloud-data-loss-prevention](<https://devfeed.tech/tags/cloud-data-loss-prevention.md>), [cloud-dataflow](<https://devfeed.tech/tags/cloud-dataflow.md>), [cloud-dataprep](<https://devfeed.tech/tags/cloud-dataprep.md>), [cloud-dataproc](<https://devfeed.tech/tags/cloud-dataproc.md>), [cloud-pub-sub](<https://devfeed.tech/tags/cloud-pub-sub.md>), [cloud-storage](<https://devfeed.tech/tags/cloud-storage.md>), [cloud-tasks](<https://devfeed.tech/tags/cloud-tasks.md>), [data-analytics](<https://devfeed.tech/tags/data-analytics.md>), [data-fusion](<https://devfeed.tech/tags/data-fusion.md>), [data-lake](<https://devfeed.tech/tags/data-lake.md>), [data-loss-prevention](<https://devfeed.tech/tags/data-loss-prevention.md>), [elt](<https://devfeed.tech/tags/elt.md>), [etl](<https://devfeed.tech/tags/etl.md>), [gcp](<https://devfeed.tech/tags/gcp.md>), [no-code](<https://devfeed.tech/tags/no-code.md>), [serverless](<https://devfeed.tech/tags/serverless.md>), [sql](<https://devfeed.tech/tags/sql.md>)

### AI overview

A practical guide to building ETL pipelines on Google Cloud Platform using Google-managed services. It explains a two-phase architecture with Cloud Storage as a data lake, Cloud Data Loss Prevention for sensitive-data detection or redaction, and BigQuery as the curated data warehouse, with attention to low-code and no-code approaches.

### Source excerpt

ETL (Extract-Transform-Load) processes are an essential component of any data analytics program. This typically involves loading data from disparate sources, transforming or enriching it, and storing the curated data in a data warehouse for consumption by different users or systems. An example of this would be taking customer data from operational databases, joining it with data from Salesforce and Google Analytics, and writing it to an OLAP database or BI engine.