Building Batch Data Pipelines on GCP em Português Brasileiro

Google Cloud via Coursera

Go to Course: https://www.coursera.org/learn/batch-data-pipelines-gcp-br

Introduction

### Course Review: Building Batch Data Pipelines on GCP em Português Brasileiro In the ever-evolving landscape of data engineering, mastering batch data pipelines is essential for professionals aiming to leverage the full potential of data in organizations. The course "Building Batch Data Pipelines on GCP em Português Brasileiro" offers a comprehensive exploration of batch data processing paradigms, tools, and best practices within Google Cloud Platform (GCP). Below is an overview, review, and recommendation for this insightful course. #### Overview The course provides a rigorous examination of the three primary paradigms of data pipelines: Extraction-Loading (EL), Extraction-Loading-Transformation (ELT), and Extract-Transform-Load (ETL). Each paradigm is contextualized to help learners understand when and how to apply these methodologies, particularly focusing on batch data processing. Throughout the course, participants dive into various GCP technologies essential for data transformation, including: - **BigQuery**: A powerful analytics data warehouse. - **Dataproc**: Managed Spark and Hadoop service. - **Cloud Data Fusion**: A robust tool for building and managing data pipelines. - **Dataflow**: A fully managed service for stream and batch processing. #### Syllabus Breakdown 1. **Introdução** - This introductory module outlines the course agenda and sets the stage for a rich learning experience. 2. **Introdução à criação de pipelines de dados em lote** - Here, learners explore different methods of data loading, including EL, ELT, and ETL. This module helps in understanding the strengths and weaknesses of each method and when to apply them effectively. 3. **Como executar o Spark no Dataproc** - This hands-on module guides users on how to execute Hadoop jobs on Dataproc, utilize Cloud Storage for data, and optimize jobs efficiently, empowering learners to harness the power of Spark within GCP. 4. **Processamento de dados sem servidor com o Dataflow** - Focusing on serverless processing, this module teaches how to build data processing pipelines with Dataflow, simplifying the complexity of resource management while maximizing processing capability. 5. **Gerenciamento de pipelines de dados com Cloud Data Fusion e Cloud Composer** - This critical module shows users how to manage and orchestrate data pipelines effectively, utilizing Cloud Data Fusion for integration and Cloud Composer for workflow management. 6. **Resumo do curso** - A concluding summary that recaps the key takeaways and reinforces the skills learned throughout the course. #### Review The **"Building Batch Data Pipelines on GCP em Português Brasileiro"** course is well-structured and provides a holistic understanding of batch data processing in the GCP ecosystem. Each module builds seamlessly upon the last, ensuring that learners develop a comprehensive skillset. **Strengths:** - **Language Accessibility**: The course is conducted in Brazilian Portuguese, making it an excellent option for native speakers and Portuguese learners. - **Hands-On Learning**: The practical modules provide real-world scenarios and practical training, which are pivotal for grasping complex concepts. - **Expert Guidance**: Instructors are knowledgeable in the field and provide insights that go beyond just theoretical knowledge. **Potential Improvements:** - Some modules could benefit from deeper dives into real-world case studies to illustrate the application of concepts learned. - Including community engagement or forums for discussion may enhance peer learning experiences. #### Recommendation I highly recommend the **"Building Batch Data Pipelines on GCP em Português Brasileiro"** course for anyone looking to deepen their understanding of data engineering on GCP. Whether you're a beginner wanting to break into the field or an experienced professional refining your skills, this course provides valuable knowledge, practical experience, and a solid foundation for building robust data pipelines. Explore this course on Coursera to unlock the potential of batch data processing and elevate your data engineering capabilities!

Syllabus

Introdução

Neste módulo, vamos apresentar o curso e a programação

Introdução à criação de pipelines de dados em lote

Este módulo analisa diferentes métodos de carregamento de dados: EL, ELT e ETL (e quando cada um deve ser usado)

Como executar o Spark no Dataproc

Este módulo mostra como executar o Hadoop no Dataproc, como usar o Cloud Storage e como otimizar os jobs do Dataproc.

Processamento de dados sem servidor com o Dataflow

Este módulo aborda o uso do Dataflow para criar pipelines de processamento de dados

Gerenciamento de pipelines de dados com

Este módulo mostra como gerenciar pipelines de dados com o Cloud Data Fusion e o Cloud Composer.

Resumo do curso

Resumo do curso