From Data to Insights with Google Cloud Platform

Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization 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 To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL.

This course teaches students the following skills:

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

Course Outline

1 - INTRODUCTION TO DATA ON THE 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
Lab: Getting started with Google Cloud Platform

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

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

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

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

6 - STORING AND EXPORTING DATA

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

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

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

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

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

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

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

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

14 - ADVANCED INSIGHTS

Introducing Cloud Datalab
Cloud Datalab Notebooks and Cells
Benefits of Cloud Datalab

15 - DATA ACCESS

Compare IAM and BigQuery Dataset Roles
Avoid Access Pitfalls
Review Members, Roles, Organizations, Account Administration, and Service Accounts

Actual course outline may vary depending on offering center. Contact your sales representative for more information.