The DBA + Data Engineering Professional Program is a comprehensive training course designed to develop advanced skills in database administration and modern data engineering practices.
This
program integrates the core concepts of database administration (DBA) with the
emerging field of data engineering. It focuses on managing enterprise-level
databases, implementing efficient data processing systems, and supporting
data-driven decision-making within organizations.
The DBA + Data Engineering Professional Program prepares learners to effectively manage modern data infrastructures and enterprise database systems. As organizations increasingly rely on data for strategic decision-making, this program provides the essential knowledge and technical skills required to succeed in today’s data-driven industry.
Objectives of the Program
· To build a strong foundation in database administration and management.
· To develop practical skills in data engineering and data pipeline development.
· To provide knowledge of data warehousing and big data technologies.
· To enable learners to manage and process large-scale data effectively.
· To prepare professionals for roles in modern data-driven industries.
• Introduction to DBMS and RDBMS
• Database architecture and components
• Data models and schema design
• Relational vs NoSQL databases
• SQL fundamentals and advanced queries
• Joins, subqueries, window functions
• Stored procedures, triggers, and views
• Query optimization techniques
• Database installation and configuration
• User management and access control
• Security and database auditing
• Database monitoring and maintenance
• Backup strategies and implementation
• Database recovery techniques
• High availability and failover systems
• Disaster recovery planning
• Indexing strategies
• Query performance tuning
• Database resource monitoring
• Performance troubleshooting
• Introduction to data engineering
• Data pipelines and ETL concepts
• Data ingestion and transformation
• Data warehousing concepts
• ETL workflow design
• Data integration techniques
• Data cleaning and transformation
• Batch and real-time data processing
• Big Data ecosystem overview
• Distributed data storage systems
• Data processing frameworks
• Large-scale data management
• Data warehouse architecture
• OLAP vs OLTP systems
• Data modeling techniques
• Data marts and reporting systems
• Cloud database services
• Data storage on cloud platforms
• Data pipeline deployment on cloud
• Cloud security and monitoring
• Shell scripting for data workflows
• Python for data engineering
• Task automation and scheduling
• Workflow orchestration tools
• Data reporting tools
• Dashboard creation
• Data visualization principles
• Business intelligence integration
• Streaming data concepts
• Event-driven data pipelines
• Real-time analytics systems
• End-to-end data pipeline development
• Database administration case study
• Cloud data engineering project
• Performance optimization project