logo
Home

From Data to Insights with Google Cloud

  • CMDBID 113826
  • Course Code GO6589
  • Duration 2 Days
Scroll

Google Cloud Course

course overview

Click to View dates & book now

Overview

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 two-day instructor-led class teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The course covers data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization.

 

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Audience

  • 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

 

Skills Gained

This course teaches participants 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

 

Prerequisites

To get the most out of this course, participants should have:

  • Basic proficiency with ANSI SQL

 

Outline

Module 1: Introduction to Data on the Google Cloud Platform

Before and Now: Scalable Data Analysis in the Cloud

Topics Covered

  • 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

Sharpen the Tools in your Data Analyst toolkit

  • 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

Get Familiar with Google BigQuery and Learn SQL Best Practices

  • 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

Calculate Google BigQuery Storage and Query Costs

  • 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

Wrangle your Raw Data into a Cleaner and Richer Dataset

  • 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

Create new Tables and Exporting Results

  • 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

Bring your Data into the Cloud

  • 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

Effectively Explore and Explain your Data through 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

Combine and Enrich your Datasets with more Data

  • 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: Google BigQuery Table Deep Dive

What sets Cloud Architecture apart?

  • Compare Data Warehouse Storage Methods
  • Deep-dive into Column-Oriented Storage
  • Examine Logical Views, Date-Partitioned Tables, and Best Practices
  • Query the Past with Time Travelling Snapshots

Module 11: Schema Design and Nested Data Structures

Model your Datasets for Scale in Google 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

Module 12: Advanced Visualization with Google Data Studio

Create Pixel-Perfect Dashboards

  • Create Case Statements and Calculated Fields
  • Avoid Performance Pitfalls with Cache considerations
  • Share Dashboards and Discuss Data Access considerations
  • Lab: Visualizing Insights with Google Data Studio

Module 13: Advanced Functions and Clauses

Dive Deeper into Advanced Query Writing with Google BigQuery

  • 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 14: Optimizing for Performance

Troubleshoot and Solve Query Performance Problems

  • 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 15: Advanced Insights

Think, Analyze, and Share Insights like a Data Scientist

  • Distill Complex Queries
  • Brainstorm Data-Driven Hypotheses
  • Think like a Data Scientist
  • Introducing Cloud Datalab
  • Lab: Reading a Google Cloud Datalab notebook

Module 16: Data Access

Keep Data Security top-of-mind in the Cloud

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

Talk to an expert

Thinking about Onsite?

If you need training for 3 or more people, you should ask us about onsite training. Putting aside the obvious location benefit, content can be customised to better meet your business objectives and more can be covered than in a public classroom. Its a cost effective option. One on one training can be delivered too, at reasonable rates.

Submit an enquiry from any page on this site, and let us know you are interested in the requirements box, or simply mention it when we contact you.

All $ prices are in USD unless it’s a NZ or AU date

SPVC = Self Paced Virtual Class

LVC = Live Virtual Class

Please Note: All courses are availaible as Live Virtual Classes

Trusted by over 1/2 million students in 15 countries

Our clients have included prestigious national organisations such as Oxford University Press, multi-national private corporations such as JP Morgan and HSBC, as well as public sector institutions such as the Department of Defence and the Department of Health.