Course CPB101:
Google Cloud Platform Serverless Data Analysis with BigQuery and Cloud Dataflow

(1 day)

Course Description

This 8-hour instructor-led course builds upon the CPB100 (which is a prerequisite). Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis, and pipeline processing.

Learning Objectives

At the end of this one-day course, participants will be able to:

Build up a complex BigQuery using clauses, inner selects, built-in functions, and joins
Load and export data to/from BigQuery
Identify need for nested, repeated fields, and user-defined functions
Understand pipeline processing, terms, and concepts
Write pipelines in Java or Python and launch them locally or in the Cloud
Implement Map Reduce transforms in Dataflow pipelines
Join datasets as side inputs
Interoperate Dataflow, BigQuery, and Cloud Pub/Sub for real-time streaming

Who Should Attend

This class is intended for data analysts and data scientists responsible for: analyzing and visualizing big data, implementing cloud-based big data solutions, deploying or migrating big data applications to the public cloud, implementing and maintaining large-scale data storage environments, and transforming/processing big data.

Prerequisites

CPB100 - Google Cloud Platform Big Data & Machine Learning Fundamentals (or equivalent experience)
Experience using a SQL-like query language to analyze data
Knowledge of either Python or Java

Modules

Module 1: BigQuery Deep Dive

A 3-hour (deep dive into details of BigQuery.
What is BigQuery?
Queries and functions + lab
Load and export data + lab
Advanced Capabilities
Performance and pricing

Module 2: Dataflow Deep Dive

A 3-hour deep dive into details of Cloud Dataflow. What is Dataflow?
Data pipeline + lab
MapReduce in Dataflow + lab
Side inputs + lab
Streaming + demo

Module 3: Summary

Where to go from here
Resources

CPB101: Google Cloud Platform Serverless Data Analysis with BigQuery and Cloud Dataflow, Virtual IST

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