Course Description
This comprehensive 5-day course equips data professionals with the skills to design, implement, and manage big data solutions for analytics. Participants will learn to architect data lakes, build fault-tolerant distributed systems, and develop scalable data processing pipelines. The course covers essential big data technologies, best practices, and real-world applications.
Learning Objectives
- Design and implement scalable big data architectures for analytics
- Build and manage data lakes using various storage technologies
- Develop efficient data processing pipelines using distributed computing frameworks
- Apply best practices for data governance, security, and quality in big data environments
- Integrate big data solutions with analytics and machine learning workflows
Course Modules
Day 1: Introduction to Big Data Engineering
- Big data concepts and ecosystem overview
- Data engineering fundamentals and best practices
- Introduction to distributed systems and parallel processing
- Big data architecture patterns and use cases
Day 2: Data Storage and Management
- Data lake design and implementation
- Distributed file systems (HDFS, S3)
- NoSQL databases for big data (MongoDB, Cassandra)
- Data modeling and schema design for big data
Day 3: Data Processing and Analytics
- Batch processing with MapReduce and Hadoop
- Stream processing with Apache Kafka and Spark Streaming
- SQL on big data with Hive and Presto
- Machine learning at scale with Spark MLlib
Day 4: Data Pipelines and Workflow Management
- ETL and data integration for big data
- Workflow orchestration with Apache Airflow
- Data quality and validation techniques
- Monitoring and optimization of data pipelines
Day 5: Advanced Topics and Best Practices
- Data governance and security in big data environments
- Performance tuning and optimization techniques
- Real-time analytics and dashboarding
- Case studies and practical applications
Practical Wins for Participants
- Design and implement a scalable data lake architecture
- Build an end-to-end data processing pipeline using distributed frameworks
- Develop a real-time analytics solution for streaming data
- Create a data governance strategy for a big data environment
Credits: 5 credit per day
Course Mode: full-time
Provider: Blackbird Training Centre
