Course Outline
Foundations of Data-Intensive Platform Engineering
- Introduction to data-intensive applications
- Challenges in platform engineering for big data
- Overview of data processing architectures
Data Modeling and Management
- Principles of data modeling for scalability
- Data storage options and optimization
- Managing data lifecycle in a distributed environment
Big Data Processing Frameworks
- Overview of big data processing tools (Hadoop, Spark, Flink)
- Batch vs. stream processing
- Setting up a big data processing pipeline
Real-Time Analytics Platforms
- Architecting for real-time analytics
- Stream processing engines (Kafka Streams, Apache Storm)
- Building real-time dashboards and visualizations
Data Pipeline Orchestration
- Workflow management with Apache Airflow and others
- Automating data pipelines for efficiency
- Monitoring and alerting for data pipelines
Platform Security and Compliance
- Security best practices for data platforms
- Ensuring data privacy and regulatory compliance
- Implementing secure data access controls
Performance Tuning and Optimization
- Techniques for optimizing data throughput and latency
- Scaling strategies for data-intensive platforms
- Performance benchmarking and monitoring
Case Studies and Best Practices
- Analyzing successful data platform implementations
- Lessons learned from industry leaders
- Emerging trends in data-intensive platform engineering
Capstone Project
- Designing a platform solution for a data-intensive application
- Implementing a prototype of the data processing pipeline
- Evaluating the platform's performance and scalability
Summary and Next Steps
Requirements
- An understanding of basic data structures and algorithms
- Experience with Java, Scala, or Python programming
- Familiarity with basic concepts of databases and SQL
Audience
- Software developers
- Data engineers
- Technical leads
Testimonials (3)
I am getting the correct level of understanding I need to assist in my day to day work
Wasfi Adams
Course - Impacted Function Point (IFP)
The trainer was super engaging and made sure we understand through questioning and affirmations. Even though the content was overwhelming, the trainer broke it down well and made content easily accessible for later reference.
Zaid Amerika
Course - Unit of Software Measurement Parameterization (UMSP)
Everything was built up from a basic level while progressing quick enough to prevent anyone getting bored.