From Data to Insights with Google Cloud Platform

Upon completion of the From Data to Insights with Google Cloud Platform course, students will be able to:

• Derive insights from data using the analysis and visualization tools on Google Cloud Platform
• Interactively query datasets using Google BigQuery
• Load, clean, and transform data at scale
• Visualize data using Google Data Studio and other third-party platforms
• Distinguish between exploratory and explanatory analytics and when to use each approach
• Explore new datasets and uncover hidden insights quickly and effectively
• Optimizing data models and queries for price and performance

• 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

• Basic proficiency with ANSI SQL (reference)

Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Intro to Google Cloud Platform

• Highlight Analytics Challenges Faced by Data Analysts
• Compare Big Data On-Premises vs on the Cloud
• Learn from Real-World Use Cases of Companies Transformed • through Analytics on the Cloud
• Navigate Google Cloud Platform Project Basics

Module 2: Analyzing Large Datasets with BigQuery

• 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: BigQuery Basics

Exploring your Public Dataset 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: Explore your Ecommerce Dataset with SQL in Google BigQuery

Cleaning and Transforming your Data with Cloud Dataprep

• 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: Creating a Data Transformation Pipeline with Cloud Dataprep

Visualizing Insights and Creating Scheduled Queries

• Overview of Data Visualization Principles
• Exploratory vs Explanatory Analysis Approaches
• Demo: Google Data Studio UI
• Connect Google Data Studio to Google BigQuery
• Lab: How to Build a BI Dashboard Using Google Data Studio and BigQuery

Storing and Ingesting new Datasets

• Compare Permanent vs Temporary Tables
• Save and Export Query Results
• Performance Preview: Query Cache
• Lab: Ingesting New Datasets into BigQuery

Enriching your Data Warehouse with JOINs

• Merge Historical Data Tables with UNION

I• ntroduce Table Wildcards for Easy Merges

• Review Data Schemas: Linking Data Across Multiple Tables
• Walkthrough JOIN Examples and Pitfalls
• Lab: Troubleshooting and Solving Data Join Pitfalls

Partitioning your Queries and Tables for Advanced Insights

• 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: Creating Date-Partitioned Tables in BigQuery

Designing Schemas that Scale: Arrays and Structs in BigQuery

• 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
• Lab: Schema Design for Performance: Arrays and Structs in BigQuery

Optimizing Queries for Performance

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

Controlling Access with Data Security Best Practices

• Data Security Best Practices
• Controlling Access with Authorized Views

Predicting Visitor Return Purchases with BigQuery ML

• Intro to ML
• Feature Selection
• Model Types
• Machine Learning in BigQuery
• Lab: Predict Visitor Purchases with a Classification Model with BigQuery ML

Deriving Insights from Unstructured Data using Machine Learning

• Structured vs Unstructured ML
• Prebuilt ML models
• Lab: Extract, Analyze, and Translate Text from Images with the Cloud ML APIs
• Lab: Training with Pre-built ML Models using Cloud Vision API and AutoML

Completion

• Summary and course wrap-up