From Data to Insights with Google Cloud Platform (GO6589)

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.


Target 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


Objectives

In this course you will learn:

  • 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
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Content

Module 1: Introduction to Data on the Google Cloud Platform

  • Before and Now: Scalable Data Analysis in the Cloud
  • Topics CoveredHighlight 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


Module 2: Big Data Tools Overview

  • Sharpen the Tools in your Data Analyst toolkit
  • Topics CoveredWalkthrough 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
  • Topics CoveredCompare 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
  • Topics CoveredWalkthrough 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
  • Topics CoveredExamine 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
  • Topics CoveredCompare 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
  • Topics CoveredQuery 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
  • Topics CoveredOverview 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
  • Topics CoveredMerge 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: Advanced Functions and Clauses

  • Dive Deeper into Advanced Query Writing with Google BigQuery
  • Topics CoveredReview 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 11: Schema Design and Nested Data Structures

  • Model your Datasets for Scale in Google BigQuery
  • Topics CoveredCompare 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: More Visualization with Google Data Studio

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


Module 13: Optimizing for Performance

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


Module 14: Advanced Insights

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


Module 15: Data Access

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