Google BigQuery: Essentials for Data Analysts

Course Overview

Google BigQuery is a fully managed, serverless data warehouse designed for large-scale data analytics. It allows users to run fast SQL queries on large datasets, providing powerful tools for analyzing and managing big data without needing to manage infrastructure. BigQuery is known for its scalability, real-time data processing, and integration with other Google Cloud services.

This course offers a comprehensive essentials to Google BigQuery and SQL. You’ll start with the fundamentals of BigQuery, including setup and navigation, before diving into SQL and query execution. Learn how to manage datasets and tables, perform data manipulations, and use advanced query techniques. The course also covers optimizing query performance and implementing best practices to maximize your efficiency with BigQuery. Ideal for those looking to enhance their data analysis skills and leverage BigQuery’s capabilities.

Launch your career in Google BigQuery by developing in-demand skills and become job-ready in 30 hours or less.  

Highlights

Upgrade your career with top notch training 

• Enhance Your Skills: Gain invaluable training that prepares you for success.
• Instructor-Led Training: Engage in interactive sessions that include hands-on exercises for practical experience.
• Flexible Online Format: Participate in the course from the comfort of your home or office.
• Accessible Learning Platform: Access course content on any device through our Learning Management System (LMS).
• Flexible Schedule: Enjoy a schedule that accommodates your personal and professional commitments.
• Job Assistance: Benefit from comprehensive support, including resume preparation and mock interviews to help you secure a position in the industry.

 Outcomes 

By the end of this course, participants will be equipped with:  

• Proficiency in BigQuery: Participants will demonstrate a thorough understanding of Google BigQuery, including its architecture, capabilities, and how it fits into the broader ecosystem of cloud data analytics.
• Connecting to Diverse Data Sources: Learners will successfully connect BigQuery to a variety of data sources, including Google Sheets, CSV files, SQL databases, and other cloud services, enabling seamless data ingestion.
• Data Preparation and Transformation Skills: Participants will gain skills in using the Query Editor for data preparation, cleaning, and transforming datasets to ensure they are ready for analysis.
• Mastery of SQL: Attendees will write, execute, and optimize SQL queries in BigQuery, using essential commands, functions, and clauses to retrieve and manipulate data effectively.
• Understanding Data Models: Learners will create and organize datasets and tables while implementing complex relationships to support data analysis.
• Advanced Query Techniques: Participants will utilize advanced querying techniques, including joining tables, using subqueries, and leveraging Common Table Expressions (CTEs) for better organization.
• Data Visualization Skills: Attendees will be able to generate insights from their data by applying best practices in data visualization, effectively presenting findings through clear and meaningful charts and dashboards.
• Familiarity with BigQuery Machine Learning: Participants will explore basic machine learning capabilities within BigQuery, including using BigQuery ML to create and evaluate predictive models.
• Deployment and Collaboration: Learners will publish reports and share insights using the Power BI Service, understanding workspace management and collaborative features.
• Insight into Performance Optimization: Participants will analyze query performance and learn best practices for optimizing their queries and managing costs effectively within BigQuery.
• Real-World Application: Through hands-on projects and case studies, learners will apply their skills to real-world datasets, enhancing their ability to solve practical business problems.
• Career Advancement: Participants will be prepared to pursue roles as data analysts or business intelligence professionals, with the skills to leverage BigQuery for data-driven decision-making.

Key Learnings in Google BigQuery

• Participants will comprehend the essential concepts of Google BigQuery, its architecture, and its role in the landscape of Big Data analytics.
• Learn how to effectively connect BigQuery to diverse data sources including Google Sheets, CSV files, SQL databases, and other cloud platforms.
• Develop a strong foundation in SQL syntax and structure, enabling participants to write efficient queries to retrieve and manipulate data.
• Learn to create, manage, and structure datasets and tables within BigQuery, understanding best practices for data organization.
• Master advanced querying techniques, such as joining tables, using subqueries, and creating Common Table Expressions (CTEs) for complex analyses.
• Apply data profiling techniques to assess data quality and insights before analysis, corresponding to business requirements.

Pre-requisites 

Participants should have general computer skills, including familiarity with MS office applications and navigating software applications.

Job roles and career paths 

This training will equip you for the following job roles and career paths: 

• Data Engineer  
• Data Analyst  
• Business Intelligence (BI) Developer  
• Data Scientist  

Google BigQuery Google BigQuery: Essentials for Data Analysts

The demand for Google BigQuery is strong because it handles large-scale data analysis efficiently. Businesses use it for its scalability, real-time processing, and integration with other Google Cloud tools. It’s popular across industries like finance, healthcare, retail, and technology, where advanced data analytics are important.