Advanced Database Engineering Program
The Advanced Database Engineering Program is designed to equip learners with in-depth expertise in database architecture, administration, optimization, and security. This program covers relational and non-relational databases, cloud database solutions, performance tuning, and data security best practices, ensuring you gain the skills required for high-demand roles in database engineering.
Course Curriculum
Module 1: Course Introduction & Database Fundamentals
- Introduction to the role of a Database Administrator (DBA) and responsibilities.
- Overview of SQL (PostgreSQL) and NoSQL (MongoDB) databases and their key differences.
- Core database concepts: tables, schemas, relationships, indexing, and data types.
- Introduction to database architecture: how data is stored, retrieved, and structured.
- Basics of database design, normalization, and data integrity.
- Course structure and real-world applications in database administration.
Module 2: Database Architecture and Management
- Deep dive into PostgreSQL architecture: processes, memory management, and storage engines.
- Understanding MongoDB architecture: collections, documents, replica sets, and sharding.
- Key indexing strategies in PostgreSQL and MongoDB for query optimization.
- Transaction management: ACID properties in SQL and BASE model in NoSQL.
- Data consistency, integrity, and performance tuning in both SQL and NoSQL environments.
- Hands-on tasks: Create and manage databases, tables, and collections efficiently.
Module 3: Cluster Setup & EC2 Instances
- Setting up AWS EC2 instances for hosting PostgreSQL and MongoDB databases.
- Installing, configuring, and managing PostgreSQL and MongoDB on EC2 instances.
- Configuring database security groups, network access, and permissions.
- Basic Linux commands for managing database files and system resources.
- Networking essentials: configuring firewalls and VPNs for secure cloud deployment.
- Real-world project: Setting up a 3-node database cluster on AWS and ensuring connectivity.
Module 4: Scaling, Replication & Security
- Vertical and horizontal scaling strategies for PostgreSQL and MongoDB.
- Setting up replication: Master-slave replication in PostgreSQL, Replica sets in MongoDB.
- High availability setup: Configuring failover, automatic recovery, and load balancing.
- Implementing security measures: user roles, encryption, SSL, and authentication.
- Backup and restore strategies: full and incremental backups at various levels.
- Real-time project: Implementing replication, scaling, and securing database clusters.
Module 5: Data Migration & Backup Solutions
- Strategies for migrating data between different environments (Prod, QA, Dev) for PostgreSQL and MongoDB.
- Tools for database migration: Use of scripts, utilities, and third-party tools.
- Backup solutions: full, differential, and incremental backups.
- Scheduling and automating backup tasks for database consistency and security.
- Using open-source tools (e.g., PerconaDB) and enterprise tools (e.g., Commvault) for backup management.
- Real-time project: Migrating data and implementing backup solutions in PostgreSQL and MongoDB.
Module 6: Monitoring, Troubleshooting & Career Readiness
- Setting up database monitoring with tools like OPSManager, PerconaDB, and MongoDB Compass.
- Performance metrics monitoring: CPU, memory, disk usage, query performance, and response times.
- Troubleshooting common issues: slow queries, database downtime, high traffic, and connection problems.
- Log analysis for optimization and identifying performance bottlenecks.
- Mock interviews, DBA-specific interview questions, and resume-building tips.
- Career guidance: Job search strategies, LinkedIn optimization, and interview preparation.
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Mongodb+postgresSQL
MongoDB, a leading NoSQL database, plays a critical role in deploying AI and machine learning applications by enabling fast, scalable data storage and retrieval. Its flexible, schema-less design allows AI systems to handle diverse, unstructured data, essential for training models and making predictions. MongoDB's ability to support real-time data updates and provide rapid access to large datasets ensures that AI applications can deliver quick, accurate responses, enhancing user experiences and operational efficiency. By using MongoDB, developers can seamlessly integrate AI models into production environments, ensuring high performance and scalability in the deployment of machine learning solutions.
Transforming the Healthcare Industry with PostgreSQL
PostgreSQL, a powerful open-source relational database management system, is revolutionizing the healthcare industry by providing secure, scalable, and efficient data management solutions. With its advanced features like ACID compliance, complex query support, and data integrity, PostgreSQL is ideal for managing the vast amounts of sensitive health data generated by hospitals, clinics, and medical research centers. It enables healthcare organizations to store patient records, medical histories, and real-time monitoring data with high reliability and security. PostgreSQL’s ability to handle structured and semi-structured data ensures seamless integration of various healthcare applications, supporting clinical decision-making, personalized treatment plans, and better overall patient care. By utilizing PostgreSQL, healthcare providers can improve data accessibility, reduce errors, and streamline operations, ultimately enhancing the quality of care and patient outcomes.
Transforming the Telecom Sector with MongoDB
MongoDB is revolutionizing the telecommunications industry by providing a flexible, scalable, and high-performance database solution to manage the vast amounts of data generated by telecom operations. Telecom companies handle diverse data types, from customer profiles and call records to network performance data and service usage patterns. MongoDB’s schema-less design allows telecom businesses to efficiently store and process this unstructured data in real-time. Its ability to scale horizontally and support high-velocity data ingestion ensures that telecom providers can handle large volumes of customer data and transactions with minimal latency. Additionally, MongoDB’s powerful aggregation framework enables telecom companies to perform complex analytics, improve network optimization, deliver personalized customer experiences, and enhance decision-making.