Data Engineering on Google Cloud Platform

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Course Overview

Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data.

Who Should Attend

Developers responsible for handling their organization's data

Course Objectives

    • Design and build data processing systems on Google Cloud Platform.
    • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc.
    • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow.
    • Derive business insights from extremely large datasets using Google BigQuery.
    • Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML.
    • Enable instant insights from streaming data

Course Outline

1 - Introduction to Data Engineering

  • Explore the role of a data engineer.
  • Analyze data engineering challenges.
  • Intro to BigQuery.
  • Data Lakes and Data Warehouses.
  • Demo: Federated Queries with BigQuery.
  • Transactional Databases vs Data Warehouses.
  • Website Demo: Finding PII in your dataset with DLP API.
  • Partner effectively with other data teams.
  • Manage data access and governance.
  • Build production-ready pipelines.
  • Review GCP customer case study.
  • Lab: Analyzing Data with BigQuery.

2 - Building a Data Lake

  • Introduction to Data Lakes.
  • Data Storage and ETL options on GCP.
  • Building a Data Lake using Cloud Storage.
  • Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions.
  • Securing Cloud Storage.
  • Storing All Sorts of Data Types.
  • Video Demo: Running federated queries on Parquet and ORC files in BigQuery.
  • Cloud SQL as a relational Data Lake.
  • Lab: Loading Taxi Data into Cloud SQL.

3 - Building a Data Warehouse

  • The modern data warehouse.
  • Intro to BigQuery.
  • Demo: Query TB+ of data in seconds.
  • Getting Started.
  • Loading Data.
  • Video Demo: Querying Cloud SQL from BigQuery.
  • Lab: Loading Data into BigQuery.
  • Exploring Schemas.
  • Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA.
  • Schema Design.
  • Nested and Repeated Fields.
  • Demo: Nested and repeated fields in BigQuery.
  • Lab: Working with JSON and Array data in BigQuery.
  • Optimizing with Partitioning and Clustering.
  • Demo: Partitioned and Clustered Tables in BigQuery.
  • Preview: Transforming Batch and Streaming Data.

4 - Introduction to Building Batch Data Pipelines,

  • EL, ELT, ETL.
  • Quality considerations.
  • How to carry out operations in BigQuery.
  • Demo: ELT to improve data quality in BigQuery.
  • Shortcomings.
  • ETL to solve data quality issues.

5 - Executing Spark on Cloud Dataproc

  • The Hadoop ecosystem.
  • Running Hadoop on Cloud Dataproc.
  • GCS instead of HDFS.
  • Optimizing Dataproc.
  • Lab: Running Apache Spark jobs on Cloud Dataproc.

6 - Serverless Data Processing with Cloud Dataflow

  • Cloud Dataflow.
  • Why customers value Dataflow.
  • Dataflow Pipelines.
  • Lab: A Simple Dataflow Pipeline (Python/Java).
  • Lab: MapReduce in Dataflow (Python/Java).
  • Lab: Side Inputs (Python/Java).
  • Dataflow Templates.
  • Dataflow SQL.

7 - Manage Data Pipelines with Cloud Data Fusion and Cloud Composer

  • Building Batch Data Pipelines visually with Cloud Data Fusion.
  • Components.
  • UI Overview.
  • Building a Pipeline.
  • Exploring Data using Wrangler.
  • Lab: Building and executing a pipeline graph in Cloud Data Fusion.
  • Orchestrating work between GCP services with Cloud Composer.
  • Apache Airflow Environment.
  • DAGs and Operators.
  • Workflow Scheduling.
  • Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery.
  • Monitoring and Logging.
  • Lab: An Introduction to Cloud Composer.

8 - Introduction to Processing Streaming Data

  • Processing Streaming Data.

9 - Serverless Messaging with Cloud Pub/Sub

  • Cloud Pub/Sub.
  • Lab: Publish Streaming Data into Pub/Sub.

10 - Cloud Dataflow Streaming Features

  • Cloud Dataflow Streaming Features.
  • Lab: Streaming Data Pipelines.

11 - High-Throughput BigQuery and Bigtable Streaming Features

  • BigQuery Streaming Features.
  • Lab: Streaming Analytics and Dashboards.
  • Cloud Bigtable.
  • Lab: Streaming Data Pipelines into Bigtable.

12 - Advanced BigQuery Functionality and Performance

  • Analytic Window Functions.
  • Using With Clauses.
  • GIS Functions.
  • Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz.
  • Performance Considerations.
  • Lab: Optimizing your BigQuery Queries for Performance.
  • Optional Lab: Creating Date-Partitioned Tables in BigQuery.

13 - Introduction to Analytics and AI

  • What is AI?.
  • From Ad-hoc Data Analysis to Data Driven Decisions.
  • Options for ML models on GCP.

14 - Prebuilt ML model APIs for Unstructured Data

  • Unstructured Data is Hard.
  • ML APIs for Enriching Data.
  • Lab: Using the Natural Language API to Classify Unstructured Text.

15 - Big Data Analytics with Cloud AI Platform Notebooks

  • Whats a Notebook.
  • BigQuery Magic and Ties to Pandas.
  • Lab: BigQuery in Jupyter Labs on AI Platform.

16 - Production ML Pipelines with Kubeflow

  • Ways to do ML on GCP.
  • Kubeflow.
  • AI Hub.
  • Lab: Running AI models on Kubeflow.

17 - Custom Model building with SQL in BigQuery ML

  • BigQuery ML for Quick Model Building.
  • Demo: Train a model with BigQuery ML to predict NYC taxi fares.
  • Supported Models.
  • Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML.
  • Lab Option 2: Movie Recommendations in BigQuery ML.

18 - Custom Model building with Cloud AutoML

  • Why Auto ML?
  • Auto ML Vision.
  • Auto ML NLP.
  • Auto ML Tables.

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Class Dates & Times

Class times are listed Mountain time

This is a 4-day class

Price (CAD): $4,932.00

Register When Time
 Register 03/04/2025 7:00AM - 3:00PM
 Register 09/09/2025 7:00AM - 3:00PM