Associate Data Practitioner

Unlock the power of your data in the cloud! Get hands-on with Google Cloud's core data services like BigQuery and Looker to validate your practical skills in data ingestion, analysis, and management, and earn your Associate Data Practitioner certification!

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3.1 Design and implement simple data pipelines

Section 3: Data Pipeline Orchestration
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Study Guides for Sub-Sections

Select a data transformation tool (e.g., Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer, Dataform) based on business requirements

Choosing the right data transformation tool on Google Cloud Platform (GCP) depends heavily on specific business requirements. There are several powerful options available,...

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Evaluate use cases for ELT and ETL

ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are two primary ways to move and prepare data in Google Cloud Platform (GCP). The main difference...

Choose products required to implement basic transformation pipelines

In designing and implementing data transformation pipelines within Google Cloud Platform (GCP), the ability to choose products that match specific requirements is crucial. To make ...