Overview

This three-day instructor-led class teaches course participants how to derive insights through data analysis and visualization using the 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 three-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, data visualization, and machine learning.

Audience

This class is intended for the following:

  • 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
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Prerequisites

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

  • Basic proficiency with ANSI SQL
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Learning Outcomes

  • Derive insights from data using the analysis and visualization tools on Google Cloud Platform
  • Load, clean, and transform data at scale with Google Cloud Dataprep
  • Explore and Visualize data using Google Data Studio
  • Troubleshoot, optimize, and write high performance queries
  • Practice with pre-built ML APIs for image and text understanding
  • Train classification and forecasting ML models using SQL with BQML
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Course Outline

Module 1: Intro to 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

Module 2: Analyzing Large Datasets with BigQuery

  • 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: BigQuery Basics

Module 3: Exploring your Public Dataset 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: Explore your Ecommerce Dataset with SQL in Google BigQuery

Module 4: Cleaning and Transforming your Data with Cloud Dataprep

  • 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: Creating a Data Transformation Pipeline with Cloud Dataprep

Module 5: Visualizing Insights and Creating Scheduled Queries

  • Overview of Data Visualization Principles
  • Exploratory vs Explanatory Analysis Approaches
  • Demo: Google Data Studio UI
  • Connect Google Data Studio to Google BigQuery
  • Lab: How to Build a BI Dashboard Using Google Data Studio and BigQuery

Module 6: Storing and Ingesting new Datasets

  1. Compare Permanent vs Temporary Tables
  2. Save and Export Query Results
  3. Performance Preview: Query Cache
  4. Lab: Ingesting New Datasets into BigQuery

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
  • Walkthrough JOIN Examples and Pitfalls
  • Lab: Troubleshooting and Solving Data Join Pitfalls

Module 8: Partitioning your Queries and Tables for Advanced Insights

  • 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: Creating Date-Partitioned Tables in BigQuery

Module 9: Designing Schemas that Scale: Arrays and Structs in 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
  • Lab: Schema Design for Performance: Arrays and Structs in BigQuery

Module 10: Optimizing Queries for Performance

  • Walkthrough of a BigQuery Job
  • Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs
  • Optimize Queries for Cost

Module 11: Controlling Access with Data Security Best Practices

  • Data Security Best Practices
  • Controlling Access with Authorized Views

Module 12: Predicting Visitor Return Purchases with BigQuery ML

  • Intro to ML
  • Feature Selection
  • Model Types
  • Machine Learning in BigQuery
  • Lab: Predict Visitor Purchases with a Classification Model with BigQuery ML

Module 13: Deriving Insights from Unstructured Data using Machine Learning

  • Structured vs Unstructured ML
  • Prebuilt ML models
  • Lab: Extract, Analyze, and Translate Text from Images with the Cloud ML APIs
  • Lab: Training with Pre-built ML Models using Cloud Vision API and AutoML

Module 14: Completion

  • Summary and course wrap-up
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Frequently asked questions

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QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

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Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.

When will I receive my certificate?

Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

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