Google Cloud Big Data
- Created By raju2006
- Last Updated December 29th, 2023
- Overview
- Prerequisites
- Audience
- Audience
- Curriculum
Description:
Explore Google Cloud's powerful big data capabilities in this introductory course. Start with a brief overview of Google Cloud and then dive deep into its robust data processing functions, unlocking the potential of data analysis and insights.
Course Code/Duration:
BDT108 / 4 Days
Learning Objectives:
After this course, you will have the opportunity to:
- Identify the purpose and value of the key Big Data fundamentals
- Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.
- Employ BigQuery and Cloud SQL to carry out interactive data analysis.
- Choose between different data processing products in Google Cloud.
Roughly one year of experience with one or more of the following:
- A common query language such as SQL.
- Extract, transform, and load activities.
- Data modelling
- Programming in Python.
- Data analysts, data scientists, and business analysts who are getting started with Google Cloud.
- Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results, and creating reports.
- Executives and IT decision makers evaluating Google Cloud for use by data scientists.
- Data analysts, data scientists, and business analysts who are getting started with Google Cloud.
- Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results, and creating reports.
- Executives and IT decision makers evaluating Google Cloud for use by data scientists.
Course Outline:
The course includes presentations, demonstrations, and hands-on labs.
Module 1: Introducing Google Cloud Platform
- Google Platform Fundamentals Overview.
- Google Cloud Platform Big Data Products.
- Lab: Sign up for Google Cloud Platform.
Module 2: Compute and Storage Fundamentals
- CPUs on demand (Compute Engine).
- A global file system (Cloud Storage).
- Cloud Shell.
- Lab: Set up an Ingest-Transform-Publish data processing pipeline.
Module 3: Data Analytics on the Cloud
- Stepping stones to the cloud.
- Cloud SQL: your SQL database on the cloud.
- Lab: Importing data into CloudSQL and running queries.
- Spark on Dataproc.
Module 4: Scaling Data Analysis
- Fast random access.
- Datalab
- BigQuery.
Module 5: Data Processing Architectures
- Message-oriented architectures with Pub/Sub.
- Creating pipelines with Dataflow.
- Reference architecture for real-time and batch data processing.
Module 6: Summary
- Why GCP?.
- Next steps
- Reference material
Training material provided:
Yes (Digital format)
The curriculum is empty
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