Big Data Storage and Management in Data Lakes
( 25 Modules )

Module #1
Introduction to Big Data and Data Lakes
Overview of big data, data lakes, and their importance in modern data analytics

Module #2
Data Lake Architecture
Understanding the components and architecture of a data lake, including ingestion, storage, and processing layers

Module #3
Big Data Storage Options
Comparison of big data storage options, including HDFS, HBase, Cassandra, and NoSQL databases

Module #4
Data Lake Storage
In-depth dive into data lake storage options, including object stores (e.g., S3, Azure Blob), file systems, and columnar storage

Module #5
Data Ingestion and Processing
Overview of data ingestion and processing concepts, including batch and stream processing, and data pipelines

Module #6
Apache NiFi and Apache Beam
Hands-on introduction to Apache NiFi and Apache Beam for building data pipelines

Module #7
Data Catalogs and Metadata Management
Understanding the importance of data catalogs and metadata management in data lakes, including data governance and quality

Module #8
Apache Hive and Presto
Introduction to Apache Hive and Presto for querying and analyzing data in data lakes

Module #9
Data Lake Security and Governance
Best practices for securing and governing data lakes, including access control, encryption, and auditing

Module #10
Data Quality and Validation
Strategies for ensuring data quality and validation in data lakes, including data profiling and data cleansing

Module #11
Data Lake Administration and Monitoring
Overview of data lake administration and monitoring, including cluster management and performance optimization

Module #12
Cloud-Based Data Lakes
Exploring cloud-based data lakes, including AWS Lake Formation, Azure Data Lake, and Google Cloud Data Lake

Module #13
On-Premises Data Lakes
Building and managing on-premises data lakes, including hardware and software considerations

Module #14
Hybrid and Edge Data Lakes
Designing and implementing hybrid and edge data lakes, including use cases and architectures

Module #15
Data Lake Use Cases and Applications
Exploring real-world use cases and applications of data lakes, including customer 360, IoT, and machine learning

Module #16
Data Lake Optimization and Tuning
Best practices for optimizing and tuning data lakes, including query optimization and storage optimization

Module #17
Data Lake Governance and Compliance
Ensuring data lake governance and compliance, including data privacy, security, and regulatory requirements

Module #18
Data Lake Architecture Patterns
Design patterns for data lake architecture, including lambda, kappa, and mediatorial patterns

Module #19
Real-Time Data Processing and Analytics
Stream processing and real-time analytics in data lakes, including Apache Kafka and Apache Flink

Module #20
Data Visualization and Reporting
Visualizing and reporting data in data lakes, including Tableau, Power BI, and D3.js

Module #21
Machine Learning and AI on Data Lakes
Building machine learning and AI models on data lakes, including data preparation and model deployment

Module #22
Data Lake Migration and Integration
Migrating and integrating data lakes with existing systems, including data warehouse and ETL integration

Module #23
Data Lake Cost Optimization and ROI
Optimizing costs and measuring ROI in data lakes, including cost analysis and TCO calculation

Module #24
Data Lake Best Practices and Troubleshooting
Best practices for data lake design, implementation, and troubleshooting, including common pitfalls and solutions

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Big Data Storage and Management in Data Lakes career

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Big Data Storage and Management in Data Lakes ( 25 Modules )

Big Data Storage and Management in Data Lakes
( 25 Modules )