Curriculum – Curs SQL Advanced & ETL Data

Descrierea cursului online SQL Advanced & ETL

Cursul de baze de date SQL Advanced & ETL Data este conceput pentru studenții care au deja o înțelegere de bază a elementelor fundamentale SQL. Aprofundăm concepte și tehnici SQL avansate, inclusiv interogări complexe, optimizarea performanței, strategii de indexare și integrarea SQL cu procesele ETL. Cursul pune accent pe înțelegerea practică a metodologiilor ETL folosind SQL ca limbaj de programare principal.

Capitole principale

1. Advanced Query Techniques

   – Subqueries

   – Common Table Expressions (CTEs)

   – Window Functions

   – Recursive Queries

 Lab Work: Write complex queries using subqueries, CTEs, and window functions to solve real-world problems such as hierarchical data representation, analytics, and reporting.

2. Advanced Joins and Set Operations

   – Outer Joins

   – Cross Joins

   – Set Operations (UNION, INTERSECT, EXCEPT)

   – Joins with Aggregations

 Lab Work: Practice advanced join techniques to combine data from multiple tables, perform set operations for data manipulation, and aggregate data efficiently.

3. Query Optimization and Performance Tuning

   – Indexing Strategies

   – Query Execution Plans

   – Query Optimization Techniques

   – Materialized Views

 Lab Work: Analyze query execution plans, identify performance bottlenecks, and implement indexing strategies to optimize query performance. Experiment with materialized views for performance enhancement.

4. Transactions and Concurrency Control

   – ACID Properties

   – Transaction Isolation Levels

   – Locking Mechanisms

   – Deadlock Detection and Prevention

Lab Work: Simulate concurrent transactions, analyze isolation levels’ impact on data consistency and performance, and implement deadlock prevention strategies.

5. Advanced Data Types and Functions

   – JSON and XML data types

   – Regular Expressions

   – User-Defined Functions

   – Stored Procedures

Lab Work: Manipulate JSON and XML data, use regular expressions for pattern matching, create user-defined functions, and develop stored procedures to encapsulate complex logic.

6. Advanced Data Modeling

   – Entity-Relationship Diagrams (ERDs)

   – Normalization and Denormalization

   – Database Design Best Practices

   – Schema Evolution

 Lab Work: Design and implement a database schema based on given requirements, apply normalization techniques, denormalize for performance optimization, and handle schema changes gracefully.

7. Introduction to ETL Processes

   – Understanding ETL Concepts

   – Extracting Data from Multiple Sources

   – Transforming Data using SQL

   – Loading Data into Target Systems

   – Creating / Editing / Monitoring Jobs

Lab Work: Design and implement basic ETL processes using SQL to extract, transform, and load data from various sources into a target database.

8. Advanced ETL Techniques

   – Incremental Loading

   – Change Data Capture (CDC)

   – Error Handling and Logging

   – Performance Optimization

Lab Work: Enhance ETL processes to support incremental loading, implement CDC mechanisms, handle errors, and optimize performance using SQL.

Follow-up Project

For the follow-up project, students will be tasked with developing a comprehensive ETL solution for a real-world scenario. This project will involve:

– Identifying data sources and destinations.

– Designing and implementing ETL processes using SQL.

– Handling various data transformations, cleansing, and enrichment tasks.

– Implementing error handling, logging, and monitoring mechanisms.

– Optimizing performance and scalability of the ETL solution.

Concluzii

La sfârșitul cursului online SQL Advanced & ETL, studenții vor avea o înțelegere profundă a conceptelor SQL avansate și experiență practică în proiectarea și implementarea proceselor ETL folosind SQL; vor fi pregătiți pentru roluri care necesită experiență în gestionarea bazelor de date, analiza datelor și dezvoltarea ETL.