From Data to Insights with Google Cloud Platform
Description
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.
Intended 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
Topics
Module 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
Module 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
Module 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
Module 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
Module 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
Module 6: Storing and Exporting Data
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
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
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
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: 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
Module 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
Module 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
Module 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
Module 14: Advanced Insights
Introducing Cloud Datalab
Cloud Datalab Notebooks and Cells
Benefits of Cloud Datalab
Module 15: Data Access
Compare IAM and BigQuery Dataset Roles
Avoid Access Pitfalls
Review Members, Roles, Organizations, Account Administration, and Service Accounts
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