Data Warehousing with BigQuery: Storage Design, Query Optimization, and administration
The Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration course is designed for students who want to deepen their BigQuery skills. The course provides a detailed overview of the BigQuery architecture and best practices for designing, optimizing, and administering your data warehouse. Students will learn how to design optimal storage and data ingestion and modification schemas. They will explore techniques for improving read performance, optimizing queries, managing workloads, and using logging and monitoring tools. The course also covers different pricing models and methods for ensuring data security, automating workloads, and building machine learning models with BigQuery ML. This course helps prepare for the Google Professional Data Engineer Certification exam .
Course Objectives
The following is a summary of the main objectives of the Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration course :
- Dive deeper into BigQuery architecture and data warehousing design practices.
- Learn query and storage performance optimization techniques.
- Manage workloads and use logging and monitoring tools.
- Understand pricing models and data security methods in BigQuery.
- Learn to build machine learning models with BigQuery ML.
- Implement best practices for schema design and data partitioning.
- Optimize data storage for cost efficiency and performance.
- Configure and manage BigQuery reservations and quotas.
Course Certification
This course helps you prepare to take the:
Google Cloud Certified Professional Data Engineer Exam;
Course Outline
Module 1: BigQuery Architecture Fundamentals
- Introduction
- BigQuery Core Infrastructure
- BigQuery Storage
- BigQuery Query Processing
- BigQuery Data Shuffling
- Labs and demos
Module 2: Storage and Schema Optimizations
- BigQuery Storage
- Partitioning and Clustering
- Nested and Repeated Fields
- ARRAY and STRUCT syntax
- Best Practices
- Labs and demos
Module 3: Ingesting Data
- Data Ingestion Options
- Batch Ingestion
- Streaming Ingestion
- Legacy Streaming API
- BigQuery Storage Write API
- Query Materialization
- Query External Data Sources
- Data Transfer Service
- Labs and demos
Module 4: Changing Data
- Managing Change in Data Warehouses
- Handling Slowly Changing Dimensions (SCD)
- DML statements
- DML Best Practices and Common Issues
- Labs and demos
Module 5: Improving Read Performance
- BigQuery’s Cache
- Materialized Views
- BI Engine
- High Throughput Reads
- BigQuery Storage Read API
- Labs and demos
Module 6: Optimizing and Troubleshooting Queries
- Simple Query Execution
- SELECTs and Aggregation
- JOINs and Skewed JOINs
- Filtering and Ordering
- Best Practices for Functions
- Labs and demos
Module 7: Workload Management and Pricing
- BigQuery Slots
- Pricing Models and Estimates
- Slot Reservations
- Controlling Costs
- Demos
Module 8: Logging and Monitoring
- Cloud Monitoring
- BigQuery Admin Panel
- Cloud Audit Logs
- Labs and demos
Module 11: Machine Learning in BigQuery
- Introduction to BigQuery ML
- How to Make Predictions with BigQuery ML
- How to Build and Deploy a Recommendation System with BigQuery ML
- How to Build and Deploy a Demand Forecasting Solution with BigQuery ML
- Time-Series Models with BigQuery ML
- BigQuery ML Explainability
- Labs and demos
Course Mode
Instructor-Led Remote Live Classroom Training;
Trainers
Trainers are GCP Official Instructors and certified in other IT technologies, with years of hands-on experience in the industry and in Training.
Lab Topology
For all types of delivery, the Trainee can access real Cisco equipment and systems in our laboratories or directly at the Cisco data centers remotely 24 hours a day. Each participant has access to implement the various configurations thus having a practical and immediate feedback of the theoretical concepts.
Here are some Labs topologies available:
Course Details
Course Prerequisites
Attendance at the Google Cloud Big Data and Machine Learning Fundamentals course is recommended .
Course Duration
Intensive duration 3 days
Course Frequency
Course Duration: 3 days (9.00 to 17.00) - Ask for other types of attendance.
Course Date
- Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration Course (Intensive Formula) – On request – 09:00 – 17:00
Steps to Enroll
Registration takes place by asking to be contacted from the following link, or by contacting the office at the international number +355 45 301 313 or by sending a request to the email info@hadartraining.com
