Overview
Data Lake Mastery using AWS: A Shortcut to Success in Big Data, Cloud Data Engineering and Data Architecture
Syllabus
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- Introduction to Data Lakes
-- Definition and key concepts
-- Data Lakes vs. Data Warehouses
-- Use cases and benefits of Data Lakes
- Architecture of Data Lakes
-- Components of a Data Lake
-- Data Ingestion and Storage
-- Metadata Management
-- Data Processing and Analytics
-- Data Governance and Security
- Building a Data Lake
-- Planning and Design
-- Selecting the right technologies and tools
-- Implementing a scalable architecture
-- Best practices for data organization and partitioning
- Cloud Data Engineering with Data Lakes
-- Overview of Cloud Providers (AWS, Azure, Google Cloud)
-- Integrating cloud services with Data Lakes
-- Cost optimization strategies
- Data Ingestion and ETL/ELT Processes
-- Batch vs. real-time data ingestion
-- Designing efficient ETL/ELT pipelines
-- Tools and platforms for data ingestion (Apache Kafka, Apache Nifi, AWS Glue)
- Data Lake Security and Compliance
-- Ensuring data privacy and protection
-- Implementing access controls and authentication
-- Compliance with regulations (GDPR, HIPAA)
- Data Management and Governance
-- Data cataloging and metadata management
-- Establishing data quality standards
-- Building a robust data governance framework
- Analyzing and Visualizing Data in Data Lakes
-- Tools for data analysis (Apache Spark, Presto)
-- Integration with BI tools (Tableau, Power BI)
-- Best practices for data visualization
- Case Studies and Real-world Applications
-- Industry-specific use cases
-- Lessons learned from successful Data Lake implementations
- Future of Data Lakes and Cloud Data Engineering
-- Emerging trends and technologies
-- The role of AI and machine learning in Data Lakes
-- Preparing for the future: skills and tools to master
- Hands-on Projects and Labs
-- Building a Data Lake from scratch
-- Implementing data ingestion and processing pipelines
-- Developing end-to-end data analysis and visualization solutions
- Conclusion and Next Steps
-- Recap of key concepts
-- Recommended resources for continued learning
-- Certification and professional development opportunities
Taught by
Tags
On-Demand
