SQL: SQL Concepts for Data Engineering
Participants will develop a strong foundation in SQL for Data Engineering, learning to manage, manipulate, and optimize large-scale structured data. They will explore relational databases, advanced SQL queries, data modeling, ETL workflows, and performance tuning techniques. Through hands-on projects, they will gain practical experience in designing scalable and efficient database solutions for Big Data applications.

Introduction to SQL for Data Engineering
  • Understand the role of SQL in Data Engineering and Big Data processing.
  • Learn about relational database management systems (RDBMS) and their architectures.
  • Explore SQL vs. NoSQL databases and their use cases in data pipelines.
Advanced SQL Querying Techniques
  • Master complex SQL queries, including joins, subqueries, and window functions.
  • Implement aggregation, grouping, and filtering techniques for large datasets.
  • Use Common Table Expressions (CTEs) and recursive queries for data transformations.
Data Modeling and Schema Design
  • Learn normalization and denormalization techniques for database optimization.
  • Design relational schemas for efficient data storage and retrieval.
  • Optimize database performance using indexing, partitioning, and constraints.
ETL and Data Pipeline Integration with SQL
  • Implement SQL-based ETL (Extract, Transform, Load) workflows.
  • Automate data ingestion and transformation using SQL and Python.
  • Integrate SQL queries with Big Data frameworks like Hadoop, Spark, and Airflow.
SQL Performance Optimization
  • Understand query execution plans and performance tuning techniques.
  • Implement indexing strategies, caching, and materialized views for efficiency.
  • Optimize SQL queries for high-volume data processing.
SQL in Cloud Data Warehousing
  • Explore cloud-based SQL solutions like Snowflake, BigQuery, and Amazon Redshift.
  • Learn how to store, query, and process data at scale in cloud environments.
  • Optimize cost and performance of SQL queries in cloud data warehouses.
Hands-On SQL Projects for Data Engineering
  • Write optimized SQL queries for large-scale data processing.
  • Develop real-world ETL pipelines using SQL for Big Data applications.
  • Design and optimize scalable data models for modern data architectures.

Der Kurs behandelt eingehend die Etablierung und Optimierung von großen relationalen Datenbanksystemen für effektive Big Data Anwendungsszenarien.