• Introduction to Data on the Google Cloud Platform

• Before and Now: Scalable Data Analysis in the Cloud
o Highlight Analytics Challenges Faced by Data Analysts
o Compare Big Data On-Premises vs on the Cloud
o Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud
o Navigate Google Cloud Platform Project Basics
o Lab: Getting started with Google Cloud Platform

• Big Data Tools Overview

• Sharpen the Tools in your Data Analyst toolkit
o Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools
o Demo: Analyze 10 Billion Records with Google BigQuery
o Explore 9 Fundamental Google BigQuery Features
o Compare GCP Tools for Analysts, Data Scientists, and Data Engineers
o Lab: Exploring Datasets with Google BigQuery

• Exploring your Data with SQL

• Get Familiar with Google BigQuery and Learn SQL Best Practices
o Compare Common Data Exploration Techniques
o Learn How to Code High Quality Standard SQL
o Explore Google BigQuery Public Datasets
o Visualization Preview: Google Data Studio
o Lab: Troubleshoot Common SQL Errors

• Google BigQuery Pricing

• Calculate Google BigQuery Storage and Query Costs
o Walkthrough of a BigQuery Job
o Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs
o Optimize Queries for Cost
o Lab: Calculate Google BigQuery Pricing

• Cleaning and Transforming your Data

• Wrangle your Raw Data into a Cleaner and Richer Dataset
o Examine the 5 Principles of Dataset Integrity
o Characterize Dataset Shape and Skew
o Clean and Transform Data using SQL
o Clean and Transform Data using a new UI: Introducing Cloud Dataprep
o Lab: Explore and Shape Data with Cloud Dataprep

• Storing and Exporting Data

• Create new Tables and Exporting Results
o Compare Permanent vs Temporary Tables
o Save and Export Query Results
o Performance Preview: Query Cache
o Lab: Creating new Permanent Tables

• Ingesting New Datasets into Google BigQuery

• Bring your Data into the Cloud
o Query from External Data Sources
o Avoid Data Ingesting Pitfalls
o Ingest New Data into Permanent Tables
o Discuss Streaming Inserts
o Lab: Ingesting and Querying New Datasets

• Data Visualization

• Effectively Explore and Explain your Data through Visualization
o Overview of Data Visualization Principles
o Exploratory vs Explanatory Analysis Approaches
o Demo: Google Data Studio UI
o Connect Google Data Studio to Google BigQuery
o Lab: Exploring a Dataset in Google Data Studio

• Joining and Merging Datasets

• Combine and Enrich your Datasets with more Data
o Merge Historical Data Tables with UNION
o Introduce Table Wildcards for Easy Merges
o Review Data Schemas: Linking Data Across Multiple Tables
o Walkthrough JOIN Examples and Pitfalls
o Lab: Join and Union Data from Multiple Tables

• Advanced Functions and Clauses

• Dive Deeper into Advanced Query Writing with Google BigQuery
o Review SQL Case Statements
o Introduce Analytical Window Functions
o Safeguard Data with One-Way Field Encryption
o Discuss Effective Sub-query and CTE design
o Compare SQL and Javascript UDFs
o Lab: Deriving Insights with Advanced SQL Functions

• Schema Design and Nested Data Structures

• Model your Datasets for Scale in Google BigQuery
o Compare Google BigQuery vs Traditional RDBMS Data Architecture
o Normalization vs Denormalization: Performance Tradeoffs
o Schema Review: The Good, The Bad, and The Ugly
o Arrays and Nested Data in Google BigQuery
o Lab: Querying Nested and Repeated Data

• More Visualization with Google Data Studio

• Create Pixel-Perfect Dashboards
o Create Case Statements and Calculated Fields
o Avoid Performance Pitfalls with Cache considerations
o Share Dashboards and Discuss Data Access considerations

• Optimizing for Performance

• Troubleshoot and Solve Query Performance Problems
o Avoid Google BigQuery Performance Pitfalls
o Prevent Hotspots in your Data
o Diagnose Performance Issues with the Query Explanation map
o Lab: Optimizing and Troubleshooting Query Performance

• Advanced Insights

• Think, Analyze, and Share Insights like a Data Scientist
o Introducing Cloud Datalab
o Cloud Datalab Notebooks and Cells
o Benefits of Cloud Datalab

• Data Access

• Keep Data Security top-of-mind in the Cloud
o Compare IAM and BigQuery Dataset Roles
o Avoid Access Pitfalls
o Review Members, Roles, Organizations, Account Administration, and Service Accounts