Become BigQuery expert by mastering Google BigQuery for data analysis. Cover all SQL qureies in PostgeSQL & Big Query
β±οΈ Length: 11.7 total hours
β 4.56/5 rating
π₯ 164,167 students
π September 2025 update
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- Course Overview
- Master Google BigQuery and PostgreSQL for advanced data analysis, bridging crucial cloud-native and traditional database environments.
- Harness Google BigQuery, Google Cloud’s scalable, serverless data warehouse, for rapid, cost-effective analysis of petabyte-scale datasets.
- Gain expertise in PostgreSQL, the robust open-source relational database, essential for transactional data and complex analytical querying.
- Strategically apply each platform’s strengths, optimizing data workflows from ingestion to actionable business intelligence for informed decision-making.
- Requirements / Prerequisites
- No prior BigQuery or PostgreSQL experience is needed; essential SQL fundamentals are thoroughly covered.
- Basic data concepts or tabular structures (e.g., spreadsheets) are helpful, not mandatory.
- Reliable internet access and a computer for cloud platform interaction are required.
- Guidance for setting up a Google Cloud Platform account (with free tiers) will be provided for hands-on exercises.
- Skills Covered / Tools Used
- BigQuery Architecture & Optimization: Deep dive into BigQuery’s serverless model, covering datasets, tables, partitioning, clustering, and advanced strategies for query optimization and cost management.
- Advanced BigQuery Data Types: Master complex data structures like ARRAYs and STRUCTs for handling semi-structured data within BigQuery.
- PostgreSQL Advanced Functions: Explore powerful PostgreSQL-specific SQL functions for sophisticated text processing, date calculations, and specialized aggregations.
- Analytical Window Functions: Apply advanced window functions (e.g., ROW_NUMBER, LAG, LEAD) across both platforms for complex ranking, sequential analysis, and cumulative metrics.
- Data Definition Language (DDL) Mastery: Confidently create, modify, and manage database schemas, tables, and views in both BigQuery and PostgreSQL.
- Query Federation & External Sources (BigQuery): Learn to query external data (e.g., Cloud Storage, Google Drive) directly from BigQuery, enabling seamless data integration without manual ETL.
- SQL Performance Tuning: Develop techniques to analyze query execution plans and optimize SQL for BigQuery and PostgreSQL, enhancing processing speed and efficiency for large datasets.
- Benefits / Outcomes
- Become a Versatile Data Expert: Acquire highly sought-after skills in both traditional and cloud-native analytics, boosting adaptability and market value across diverse data roles.
- Drive Strategic Insights: Master extracting, transforming, and analyzing large datasets to generate critical business intelligence, influencing strategic business decision-making.
- Excel in Cloud Data Roles: Gain specialized BigQuery expertise, becoming a key asset for organizations leveraging cloud infrastructure for their advanced analytical needs.
- Build a Professional SQL Portfolio: Complete practical projects showcasing advanced SQL, data modeling, and analytical problem-solving skills for career advancement.
- Optimize Data Operations: Learn to write efficient and cost-effective SQL queries, minimizing cloud expenditure and maximizing data processing performance.
- Enhanced Career Trajectory: Open doors to advanced positions in Data Analytics, BI Development, Data Engineering, and Data Science with industry-leading tool expertise.
- PROS
- Comprehensive Dual-Platform Mastery: Uniquely combines PostgreSQL and BigQuery skills, offering high versatility for modern data roles.
- High Market Demand: Focuses on critical industry technologies, boosting employability and career growth.
- Proven Quality & Popularity: Excellent ratings and large enrollment signify a highly effective learning experience.
- Up-to-Date Curriculum: Regularly refreshed content ensures mastery of the latest features and best practices for both databases.
- CONS
- Requires Consistent Self-Practice: Mastery of complex SQL concepts and platform specifics necessitates dedicated, ongoing practice beyond course material.
Learning Tracks: English,Business,Business Analytics & Intelligence
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