Building Resilient Streaming Analytics Systems on GCP 日本語版

Google Cloud via Coursera

Go to Course: https://www.coursera.org/learn/streaming-analytics-systems-gcp-jp

Introduction

## Course Review: Building Resilient Streaming Analytics Systems on GCP 日本語版 In today's digital age, real-time data processing is pivotal for businesses seeking to gain insights and drive decisions through analytics. The "Building Resilient Streaming Analytics Systems on GCP 日本語版" course on Coursera stands out as an excellent resource for professionals aiming to develop their skills in handling streaming data using Google Cloud Platform (GCP). ### Overview This course is specifically designed for individuals interested in learning how to construct streaming data pipelines that enable companies to monitor real-time indicators affecting their operations. Conducted in Japanese, it provides a detailed exploration of several essential components, which include Pub/Sub for ingesting streaming data, Dataflow for aggregating and transforming the data, and the best storage options like BigQuery and Cloud Bigtable for processed records. Participants will benefit from hands-on experience, employing Qwiklabs to construct components of a streaming data pipeline on GCP. The course's practical approach ensures that learners not only understand theoretical concepts but also gain valuable real-world skills that are immediately applicable. ### Syllabus Breakdown The course is structured into several modules that encapsulate critical components of streaming data processing: 1. **Introduction**: This module presents an overview of the course and its agenda, setting the stage for what learners can expect. 2. **Overview of Streaming Data Processing**: Participants delve into the challenges associated with processing streaming data, gaining insights into the complexities that they may face in real-world applications. 3. **Serverless Messaging with Pub/Sub**: This module focuses on how to leverage Pub/Sub for ingesting incoming streaming data effectively, introducing learners to serverless messaging frameworks. 4. **Streaming Capabilities of Dataflow**: Attendees will revisit the Dataflow service, emphasizing its powerful capabilities for streaming data processing. 5. **High Throughput Streaming with Cloud Bigtable**: This section discusses optimal storage solutions for streaming data, focusing on the use of BigQuery and Bigtable to manage large datasets efficiently. 6. **Advanced BigQuery Features and Performance**: Here, learners will explore advanced functionalities of BigQuery, enhancing their analytical capabilities and performance tuning skills. 7. **Course Summary**: This concluding module wraps up the course by revisiting all the topics covered, reinforcing learning and preparing participants for application in their work environments. ### Why You Should Take This Course 1. **Hands-on Learning**: The inclusion of Qwiklabs allows for practical application of theoretical knowledge, making the learning experience robust and valuable. 2. **Industry-Relevant Skills**: The course equips learners with the skills needed in today's job market, making it an excellent investment for career advancement. 3. **Network with Peers**: Engaging with other learners offers opportunities for networking, collaboration, and sharing insights, which enhances the learning experience. 4. **Flexibility**: Being an online course, it provides the flexibility to learn at your own pace, which is particularly beneficial for working professionals. ### Recommendation I highly recommend the "Building Resilient Streaming Analytics Systems on GCP 日本語版" course for anyone looking to enhance their knowledge and skills in streaming data processing on Google Cloud Platform. Whether you are a data analyst, cloud engineer, or simply passionate about data analytics, this course provides a comprehensive learning path that equips you with essential tools and techniques to build resilient analytics systems. Embrace the opportunity to learn and transform your professional capabilities in one of the most sought-after skill sets in the tech industry today!

Syllabus

はじめに

このモジュールでは、コースおよびアジェンダについて紹介します

ストリーミング データの処理に関する概要

このモジュールでは、ストリーミング データの処理に伴う課題について説明します

Pub/Sub を使用したサーバーレス メッセージング

このモジュールでは、Pub/Sub を使用した受信ストリーミング データを取り込みについて説明します

Dataflow のストリーミング機能

このモジュールでは、Dataflow について再確認し、そのストリーミング データ処理機能に焦点を当てます

Cloud Bigtable を使用した高スループットのストリーミング

このモジュールでは、ストリーミング データに適した BigQuery と Bigtable について説明します

高度な BigQuery の機能とパフォーマンス

このモジュールでは、BigQuery のより高度な機能について詳しく説明します

コースのまとめ

このモジュールでは、コースで扱ったトピックについて復習します