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Course Outline
Foundations of Data-Intensive Platform Engineering for Government
- Introduction to data-intensive applications in government environments
- Challenges in platform engineering for big data within the public sector
- Overview of data processing architectures suitable for government use
Data Modeling and Management for Government
- Principles of data modeling for scalability in governmental systems
- Data storage options and optimization tailored to public sector needs
- Managing the data lifecycle in a distributed environment within government agencies
Big Data Processing Frameworks for Government
- Overview of big data processing tools (Hadoop, Spark, Flink) suitable for government applications
- Batch vs. stream processing in the context of public sector requirements
- Setting up a big data processing pipeline aligned with government workflows
Real-Time Analytics Platforms for Government
- Architecting real-time analytics platforms to meet government needs
- Stream processing engines (Kafka Streams, Apache Storm) optimized for public sector use
- Building real-time dashboards and visualizations for enhanced decision-making in government
Data Pipeline Orchestration for Government
- Workflow management with tools like Apache Airflow tailored for government operations
- Automating data pipelines to enhance efficiency in public sector workflows
- Monitoring and alerting mechanisms designed for government data pipelines
Platform Security and Compliance for Government
- Security best practices for data platforms within the public sector
- Ensuring data privacy and regulatory compliance in government environments
- Implementing secure data access controls to meet government standards
Performance Tuning and Optimization for Government
- Techniques for optimizing data throughput and latency in governmental systems
- Scaling strategies for data-intensive platforms aligned with public sector requirements
- Performance benchmarking and monitoring tailored to government operations
Case Studies and Best Practices for Government
- Analyzing successful data platform implementations within the public sector
- Lessons learned from industry leaders in government data management
- Emerging trends in data-intensive platform engineering relevant to government agencies
Capstone Project for Government
- Designing a platform solution for a data-intensive application within the public sector
- Implementing a prototype of the data processing pipeline tailored for government use
- Evaluating the platform's performance and scalability in a government context
Summary and Next Steps for Government
Requirements
- An understanding of fundamental data structures and algorithms
- Experience with Java, Scala, or Python programming languages
- Familiarity with basic database concepts and SQL
Audience for government
- Software developers
- Data engineers
- Technical leads
21 Hours
Testimonials (1)
About the microservices and how to maintenance kubernetes