From Data to Insights with Google Cloud

– • Joining and Merging Datasets: Combine and Enrich Datasets with More Data
– • Advanced Functions and Clauses: Dive Deeper into Advanced Query Writing with Google BigQuery
– • Data Visualization: Effectively Explore and Explain Data through Visualization
– • Ingesting New Datasets into Google BigQuery: Bring your Data into the Cloud
– • Optimizing for Performance: Troubleshoot and Solve Query Performance Problems
– • How Google does Machine Learning: Leverage pre-built ML APIs for your projects
– • Applying Machine Learning to your Datasets (BQML)
– • Data Access: Keep Data Security Top-of-Mind in the Cloud
– • Schema Design and Nested Data Structures: Model Datasets for Scale in Google BigQuery
– • More Visualization with Google Data Studio: Create Pixel-Perfect Dashboards
– • Introduction to Data on Google Cloud
– • Analyzing Large Datasets with BigQuery
– • Exploring your Public Dataset with SQL
– • Cleaning and Transforming your Data with Dataprep
– • Visualizing Insights and Creating Scheduled Queries
– • Storing and Ingesting New Datasets
– • Enriching your Data Warehouse with JOINs
– • Advanced Features and Partitioning your Queries and Tables for Advanced Insights
– • Designing Schemas that Scale: Arrays and Structs in BigQuery
– • Optimizing Queries for Performance
– • Controlling Access with Data Security
– • Predicting Visitor Return Purchases with BigQuery ML
– • Deriving Insights From Unstructured Data Using Machine Learning
– • Big Data Tools Overview: Sharpen the Tools in your Data Analyst toolkit
– • Introduction to Data on the Google Cloud Platform: Before and Now – Scalable Data Analysis in the Cloud
– • Exploring your Data: Get Familiar with Google BigQuery and Learn SQL Best Practices
– • Cleaning and Transforming your Data: Wrangle your Raw Data into a Cleaner and Richer Dataset
– • Google BigQuery Pricing: Calculate Google BigQuery Storage and Query Costs
– • Storing and Exporting Data: Create new Tables and Exporting Results