Course #: GCP-320
Duration: 3 Days
Price: 2,241.00 USD
Prices reflect a 20% discount for IBM employees
Prices shown are the special AWS Partner Price
Prices reflect the Capgemini employee discount
Prices reflect the UPS employee discount
Prices reflect the employee discount
GSA Public Price: ??gsa-public-price??
GSA Private/Onsite Price: ??gsa-private-price??
For GSA pricing, go to GSA Advantage!
Delivery Formats
Material: LearnGreen (pdf)
This course is eligible for the IBM Full Access Training Pass. Get your subscription for a full year.
Filter Area Unfilter
Classroom Schedule
Virtual Schedule Virtual Training Facts
Close
9AM - 5PM
US Eastern
9AM - 5PM
US Eastern
Not seeing what you want? Contact us
Not seeing what you want? Contact us
Classroom Schedule
Virtual Schedule
Close
There are no virtual classes on the schedule in your country.
There are no public classes currently scheduled in your country.
View our global class schedule
This course is available in private, mentoring or e-learning options.
Complete this form, and a Training Advisor will be in touch with you shortly to address your training needs.
By submitting this form, I agree to LearnQuest's Terms and Conditions
Request Private Training
Close
Tell us a little about yourself:
By submitting this form, I agree to LearnQuest's Terms and Conditions
All Courses Backed by the LearnQuest 100% Satisfaction Guarantee
Course Description
Objectives
- 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
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
Prerequisites
- Basic proficiency with ANSI SQL (reference)
Topics
- 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
- 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
- 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
- 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
- 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
- Compare Permanent vs Temporary Tables
- Save and Export Query Results
- Performance Preview: Query Cache
- Lab: Ingesting New Datasets into BigQuery
- Merge Historical Data Tables with UNION
- Review Data Schemas: Linking Data Across Multiple Tables
- Walkthrough JOIN Examples and Pitfalls
- Lab: Troubleshooting and Solving Data Join Pitfalls
- 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
- 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
- Walkthrough of a BigQuery Job
- Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs
- Optimize Queries for Cost
- Data Security Best Practices
- Controlling Access with Authorized Views
- Intro to ML
- Feature Selection
- Model Types
- Machine Learning in BigQuery
- Lab: Predict Visitor Purchases with a Classification Model with BigQuery ML
- 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
- Summary and course wrap-up
Related Courses










Reviews

We Guarantee You'll be Satisfied
At LearnQuest, our goal is always the same: to provide the highest quality training and service to each and every customer.
If you’re not satisfied for any reason, simply contact one of our Training Advisors for assistance with your concerns.

Enrollment Options
Select the Training Provider you would like to use
Already have an account? Login here >
You will be leaving the LearnQuest Website
*If using Apple Training Credits or LearnPass, you must enroll with LearnQuest