From Data to Insights with Google Cloud Platform

Course subjects

Module 1: Introduction to Data on the Google Cloud

• Analytics Challenges Faced by Data Analysts

• Big Data On-Premise vs on the Cloud

• Real-World Use Cases of Companies Transformed through Analytics on the Cloud

• Google Cloud Project Basics

Module 2: Analysing Large Datasets with BigQuery

• Data Analyst Tasks, Challenges, and Google Cloud Data Tools

• Fundamental BigQuery Features

• Google Cloud Tools for Analysts, Data Scientists, and Data Engineers

Module 3: Exploring your Public Dataset with SQL

• Common Data Exploration Techniques

• Use SQL to Query Public Datasets

Module 4: Cleaning and Transforming your Data with Dataprep

• 5 Principles of Dataset Integrity

• Dataset Shape and Skew

• Clean and Transform Data using SQL

• Introducing Dataprep by Trifacta

Module 5: Visualising Insights and Creating Scheduled Queries

• Data Visualisation Principles

• Common Data Visualisation Pitfalls

• Looker Studio

Module 6: Storing and Ingesting New Datasets

• Permanent vs Temporary Data Tables

• Ingesting New Datasets

Module 7: Enriching your Data Warehouse with JOINs

• Merge Historical Data Tables with UNION

• Introduce Table Wildcards for Easy Merges

• Review Data Schemas: Linking Data Across Multiple Tables

• JOIN Examples and Pitfalls

Module 8: Advanced Features and Partitioning your Queries and Tables
for Advanced Insights

• Advanced Functions (Statistical, Analytic, User-defined)

• Date-Partitioned Tables

Module 9: Designing Schemas that Scale: Arrays and Structs in BigQuery

• BigQuery Versus Traditional Relational Data Architecture

• ARRAY and STRUCT Syntax

• BigQuery Architecture

Module 10: Optimising Queries for Performance

• BigQuery Performance Pitfalls

• Prevent Data Hotspots

• Diagnose Performance Issues with the Query Explanation Map

Module 11: Controlling Access with Data Security Best Practices

• Hashing Columns

• Authorised Views

• IAM and BigQuery Dataset Roles

• Access Pitfalls

Module 12: Predicting Visitor Return Purchases with BigQuery ML

• Machine Learning on Structured Data

• Scenario: Predicting Customer Lifetime Value

• Choosing the Right Model Type

• Creating ML models with SQL

Module 13: Deriving Insights From Unstructured Data Using Machine Learning

• ML Drives Business Value

• How does ML on Unstructured Data Work?

• Choosing the Right ML Approach

• Pre-built AI Building Blocks

• Customising Pre-built Models with AutoML

• Building a Custom Model