Data to Insights with 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 two-day, instructor-led course teaches 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.
- » Data Analyst professionals
- » Business Analyst professionals
- » 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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- » 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
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- Introduction to Data on the Google Cloud Platform (Before and Now: Scalable Data Analysis in the Cloud)
- 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
- 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
- Exploring your Data (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
- 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
- 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
- Storing and Exporting Data (Create new Tables and Exporting Results)
- Compare Permanent vs. Temporary Tables
- Save and Export Query Results
- Performance Preview: Query Cache
- 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
- Data Visualization (Effectively Explore and Explain 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
- Joining and Merging Datasets (Combine and Enrich 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
- Google BigQuery Tables 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
- Schema Design and Nested Data Structures (Model Datasets for Scale in Google BigQuery)
- Compare Google BigQuery vs. Traditional RDBMS Data Architecture
- Normalization vs. Denormalization: Performance Trade-Offs
- Schema Review: The Good, The Bad, and The Ugly
- Arrays and Nested Data in Google BigQuery
- 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
- 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
- Optimizing for Performance (Troubleshoot and Solve Query Performance Problems)
- Avoid Google BigQuery Performance Pitfalls
- Prevent Hotspots in Data
- Diagnose Performance Issues with the Query Explanation Map
- 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
- 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
- Getting Started with Google Cloud Platform
- Exploring Datasets with Google BigQuery
- Troubleshoot Common SQL Errors
- Calculate Google BigQuery Pricing
- Explore and Shape Data with Cloud Dataprep
- Creating New Permanent Tables
- Ingesting and Querying New Datasets
- Exploring a Dataset in Google Data Studio
- Join and Union Data from Multiple Tables
- Querying Nested and Repeated Data
- Visualizing Insights with Google Data Studio
- Deriving Insights with Advanced SQL Functions
- Optimizing and Troubleshooting Query Performance
- Reading a Google Cloud Datalab Notebook
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We ensure your success by asking all
students to take a FREE Skill Assessment test.
These short, instructor-written tests are an objective measure of your current skills that help us determine whether or not you will be able to meet your goals by attending this course at your current skill level. If we determine that you need additional preparation or training in order to gain the most value from this course, we will recommend cost-effective solutions that you can use to get ready for the course.
Our required skill-assessments ensure that:
- All students in the class are at a comparable skill level, so the class can run smoothly without beginners slowing down the class for everyone else.
- NetCom students enjoy one of the industry's highest success rates, and pass rates when a certification exam is involved.
- We stay committed to providing you real value. Again, your success is paramount; we will register you only if you have the skills to succeed.
This assessment is for your benefit and best taken without any preparation or reference materials, so your skills can be objectively measured.
Take your FREE Skill Assessment test »
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- Developed the first online multimedia training content system to Harvard University as well as multiple online multimedia projects for the North Carolina State Government.
- Highly rated instructor averaging 8.7 out of 9 on evaluation reports.
Erick has been training business and IT professionals since 1989, when he developed and introduced the first online multimedia training content system to Harvard University. Since then he has honed his business, programming, and database skills providing highly customized software solutions and education programs for multiple clients such as North Carolina State Government, Cisco, IBM, and Time Warner Cable.
Erick's teaching prowess and real-world experience leading a team of software application developers make him a top Instructor and Subject Matter Expert at NetCom Learning, where he averages 8.7 out of 9 on evaluation reports.
- Team leader for the first undergraduate team to win the Duke Startup Challenge.
- Over 15 years of experience in the IT industry.
- NetCom Learning Instructor of the Year 2011.
Sam Polsky has spent his entire career in entrepreneurial pursuits, including such fields as biotechnology, software development, data management, and business process management. He began in entrepreneurship as team leader for the first undergraduate team to win the Duke Startup Challenge, a business development competition geared towards Duke Universitys various graduate schools.
Sam Polsky has since co-founded a consulting firm where he has been involved in software architecture, development and implementation. On top of that, Sam has been delivering acclaimed solutions in software architecture, development and implementation for over 15 years. He is a much-admired Subject Matter Expert and Trainer at NetCom Learning and was voted NetCom Learning Instructor of the Year 2011
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