Cloud Architecture
From Data to Insights with Google Cloud
Gain a solid understanding of BigQuery fundamentals and unlock the power of Google Cloud for advanced data insights. Learn to analyze and visualize data to derive detailed and actionable insights in this hands-on course
3 Days
Target Audience
Whether you’re a data analyst, business intelligence expert, or a cloud data engineer partnering with analysts, this course provides the tools and knowledge you need to excel with BigQuery and Google Cloud
What you'll learn
Data Insights:
Analyze, clean, and visualize data with Dataprep and Data Studio.
High-Performance Queries:
Optimize BigQuery for efficient querying.
ML Integration:
Use ML APIs and BigQuery ML for forecasting and classification.
Prerequisites for Success
Prerequisites for Success
You should have a basic proficiency with ANSI SQL. This foundational knowledge will enable you to grasp advanced concepts and apply them effectively throughout the course
COURSE AGENDA
Introduction to Google Cloud
- Explore analytics challenges faced by data analysts.
- Compare Big Data solutions on-premises versus in the Cloud.
- Learn from real-world examples of companies transformed through Cloud Analytics.
- Navigate Google Cloud project basics.
Analyzing Large Datasets with BigQuery
- Understand data analyst tasks and challenges, and discover Google Cloud Data Tools.
- Demo: Analyze 10 billion records using Google BigQuery.
- Explore key BigQuery features for large-scale analytics.
- Compare Google Cloud tools for analysts, data scientists, and data engineers.
Exploring Public Datasets with SQL
- Compare common data exploration techniques.
- Master basic SQL SELECT statements and avoid common pitfalls.
- Use SQL functions to create calculated fields.
- Explore Google BigQuery public datasets.
- Preview data visualizations with Google Data Studio.
Cleaning & Transforming Data with Cloud Dataprep
- Learn the five principles of dataset integrity.
- Analyze dataset shape and skew.
- Clean and transform data using SQL and the Cloud Dataprep UI.
Visualizing Insights & Creating Scheduled Queries
- Understand principles of effective data visualization.
- Avoid common data visualization pitfalls.
- Leverage tools like Looker Studio for creating visualizations and scheduled queries.
Storing & Ingesting New Datasets
- Compare permanent and temporary tables in BigQuery.
- Learn methods for ingesting new datasets.
Enriching Your Data Warehouse with JOINs
- Merge historical data tables using UNION.
- Use table wildcards for efficient data merging.
- Link data across multiple tables by reviewing schemas and JOIN examples.
Advanced Features & Partitioning Queries and Tables
- Leverage advanced SQL functions, including statistical, analytic, and user-defined functions.Use date-partitioned tables for advanced query optimization.
Designing Schemas that Scale with Arrays & Structs
- Compare BigQuery’s data architecture to traditional relational architectures.
- Learn to use ARRAY and STRUCT syntax for efficient schema design.
Optimizing Queries for Performance
- Identify BigQuery performance pitfalls and avoid data hotspots.Diagnose performance issues using the query explanation map.
Controlling Access with Data Security Best Practices
- Implement hashing for sensitive columns.
- Control access using authorized views, IAM roles, and dataset permissions.
- Highlight common data access pitfalls.
Predicting Visitor Return Purchases with BigQuery ML
- Discover how machine learning on structured data drives value.
- Predict customer LTV with appropriate ML models.
- Build ML models using SQL with BigQuery ML.
Deriving Insights from Unstructured Data Using Machine Learning
- Learn how ML on unstructured data works.
- Choose the right ML approach for your data.
- Leverage pre-built AI building blocks and customize models with AutoML.
- Build custom ML models tailored to your needs.