Explore ways to derive insights from data at scale using BigQuery, Google Cloud’s serverless, highly scalable, and cost-effective cloud data warehouse.
This course uses lectures, demos, and hands-on labs to teach you the fundamentals of BigQuery, including how to create a data transformation pipeline, build a BI dashboard, ingest new datasets, and design schemas at scale.
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What you’ll learn
This course teaches participants the following skills:
Derive insights from data using the analysis and visualization tools on Google Cloud Platform
Load, clean, and transform data at scale with Google Cloud Dataprep
Explore and Visualize data using Google Data Studio
Troubleshoot, optimize, and write high performance queries
Practice with pre-built ML APIs for image and text understanding
Train classification and forecasting ML models using SQL with BQML
Google Cloud at DDLS
DDLS is Australia's only national Google Cloud Authorised Training Partner. Get the skills needed to build, test and deploy applications on this highly scalable infrastructure. Engineered to handle the most data-intensive work you can throw at it, DDLS can support you through training wherever you are in your Cloud adoption journey.
From our state-of-the-art classrooms to telepresence to your offices, our instructor-led training caters to your needs.
Track Record
30 years driving innovative, award-winning learning solutions
More Courses, More Often
When you train with DDLS you get more courses, more often, in more locations and from more vendors.
Quality instructors and content
Expert instructors with real world experience and the latest vendor- approved in-depth course content.
Partner-Preferred Supplier
Chosen and awarded by the world’s leading vendors as preferred training partner.
Ahead of the technology curve
No matter your chosen technologies or platforms, we can help you stay one step ahead.
Train Anywhere
From our state-of-the-art classrooms to telepresence to your offices, our instructor-led training caters to your needs.
Track Record
30 years driving innovative, award-winning learning solutions
More Courses, More Often
When you train with DDLS you get more courses, more often, in more locations and from more vendors.
Quality instructors and content
Expert instructors with real world experience and the latest vendor- approved in-depth course content.
Partner-Preferred Supplier
Chosen and awarded by the world’s leading vendors as preferred training partner.
Ahead of the technology curve
No matter your chosen technologies or platforms, we can help you stay one step ahead.
Train Anywhere
From our state-of-the-art classrooms to telepresence to your offices, our instructor-led training caters to your needs.
Track Record
30 years driving innovative, award-winning learning solutions
More Courses, More Often
When you train with DDLS you get more courses, more often, in more locations and from more vendors.
Who is the course for?
This course is intended for the following participants:
Data Analysts, Business Analysts, Business Intelligence professionals
Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform
Course subjects
Module 1: Introduction to Data on the Google Cloud Platform
Highlight Analytics Challenges Faced by Data Analysts
Compare Big Data On-Premise vs on the Cloud
Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud
Navigate Google Cloud Platform Project Basics
Lab: Getting started with Google Cloud Platform
Module 2: Big Data Tools Overview
Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools
Demo: Analyze 10 Billion Records with Google BigQuery
Explore 9 Fundamental Google BigQuery Features
Compare GCP Tools for Analysts, Data Scientists, and Data Engineers
Lab: Exploring Datasets with Google BigQuery
Module 3: Exploring your Data with SQL
Compare Common Data Exploration Techniques
Learn How to Code High Quality Standard SQL
Explore Google BigQuery Public Datasets
Visualization Preview: Google Data Studio
Lab: Troubleshoot Common SQL Errors
Module 4: Google BigQuery Pricing
Walkthrough of a BigQuery Job
Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs
Optimize Queries for Cost
Lab: Calculate Google BigQuery Pricing
Module 5: Cleaning and Transforming your Data
Examine the 5 Principles of Dataset Integrity
Characterize Dataset Shape and Skew
Clean and Transform Data using SQL
Clean and Transform Data using a new UI: Introducing Cloud Dataprep
Lab: Explore and Shape Data with Cloud Dataprep
Module 6: Storing and Exporting Data
Compare Permanent vs Temporary Tables
Save and Export Query Results
Performance Preview: Query Cache
Lab: Creating new Permanent Tables
Module 7: Ingesting New Datasets into Google BigQuery
Query from External Data Sources
Avoid Data Ingesting Pitfalls
Ingest New Data into Permanent Tables
Discuss Streaming Inserts
Lab: Ingesting and Querying New Datasets
Module 8: Data Visualization
Overview of Data Visualization Principles
Exploratory vs Explanatory Analysis Approaches
Demo: Google Data Studio UI
Connect Google Data Studio to Google BigQuery
Lab: Exploring a Dataset in Google Data Studio
Module 9: Joining and Merging Datasets
Merge Historical Data Tables with UNION
Introduce Table Wildcards for Easy Merges
Review Data Schemas: Linking Data Across Multiple Tables
Walkthrough JOIN Examples and Pitfalls
Lab: Join and Union Data from Multiple Tables
Module 10: Advanced Functions and Clauses
Review SQL Case Statements
Introduce Analytical Window Functions
Safeguard Data with One-Way Field Encryption
Discuss Effective Sub-query and CTE design
Compare SQL and JavaScript UDFs
Lab: Deriving Insights with Advanced SQL Functions
Module 11: Schema Design and Nested Data Structures
Compare Google BigQuery vs Traditional RDBMS Data Architecture
Normalization vs Denormalization: Performance Tradeoffs
Schema Review: The Good, The Bad, and The Ugly
Arrays and Nested Data in Google BigQuery
Lab: Querying Nested and Repeated Data
Module 12: More Visualization with Google Data Studio
Create Case Statements and Calculated Fields
Avoid Performance Pitfalls with Cache considerations
Share Dashboards and Discuss Data Access considerations
Module 13: Optimizing for Performance
Avoid Google BigQuery Performance Pitfalls
Prevent Hotspots in your Data
Diagnose Performance Issues with the Query Explanation map
Lab: Optimizing and Troubleshooting Query Performance
Module 14: Data Access
Compare IAM and BigQuery Dataset Roles
Avoid Access Pitfalls
Review Members, Roles, Organizations, Account Administration, and Service Accounts
Module 15: Notebooks in the Cloud
Cloud Datalab
Compute Engine and Cloud Storage
Lab: Rent-a-VM to process earthquakes data
Data Analysis with BigQuery
Module 16: How Google does Machine Learning
Introduction to Machine Learning for analysts
Practice with Pretrained ML APIs for image and text understanding
Lab: Pretrained ML APIs
Module 17: Applying Machine Learning to your Datasets (BQML)
Building Machine Learning datasets and analyzing features
Creating classification and forecasting models with BQML
Lab: Predict Visitor Purchases with a Classification Model in BQML
Lab: Predict Taxi Fare with a BigQuery ML Forecasting Model
Prerequisites
To get the most out of this course, participants should have:
Basic proficiency with ANSI SQL
Terms & Conditions
The supply of this course by DDLS is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
Request Course Information
By submitting an enquiry, you agree to our privacy policy and receiving email and other forms of communication from us. You can opt-out at any time.
