Big Data Engineering with Data Modeling and Architecture

Duration: Hours



    Training Mode: Online


    This comprehensive training program offers a deep dive into the realm of Big Data engineering, focusing on data modeling and architecture to equip participants with the skills and knowledge needed to tackle complex data challenges at Locus Academy .

    Through a blend of theoretical concepts and practical hands-on exercises, participants will learn how to design robust data models, architect scalable Big Data systems, and optimize data pipelines for efficient processing and analysis. The training covers key topics such as conceptual, logical, and physical data modeling, data warehouse design principles, distributed computing frameworks, and best practices for managing and governing Big Data environments.

    Participants will also explore advanced techniques for data integration, data governance, and data quality assurance to ensure the reliability and integrity of large-scale data systems. By the end of the training, participants will be equipped with the expertise to design, implement, and manage data-centric solutions that meet the evolving demands of modern enterprises in the era of Big Data.


    1. Introduction to Big Data

    Definition of Big Data
    Characteristics and challenges of Big Data
    Importance and applications of Big Data in various industries

    2. Basics of Data Management

    Data types and structures
    Relational databases
    NoSQL databases
    Data normalization and denormalization

    3. Distributed Systems

    Fundamentals of distributed computing
    Distributed storage and processing
    Cluster computing
    Fault tolerance and scalability

    4. Big Data Technologies and Tools

    Hadoop ecosystem (HDFS, MapReduce, YARN)
    Apache Spark
    Apache Flink
    Data warehousing solutions

    5. Data Processing and Analysis

    Batch processing vs. real-time processing
    Data cleaning and preprocessing
    Data transformation and enrichment
    Stream processing

    6. Data Modeling and Architecture

    Big Data architecture
    Data modeling for Big Data
    Data integration and orchestration
    Lambda architecture and Kappa architecture

    7. Cloud Computing for Big Data

    Cloud-based storage solutions
    Cloud-based data processing platforms
    Serverless computing
    Case studies of using cloud platforms for Big Data

    8. Data Security and Privacy

    Challenges in securing Big Data
    Encryption and access control
    Compliance with data protection regulations
    Best practices for ensuring data privacy

    9. Real-world Big Data Applications

    Case studies and use cases
    Industry-specific applications (e.g., healthcare, finance, retail)
    Success stories and lessons learned

    10. Capstone Project

    Hands-on project involving the design and implementation of a Big Data solution
    Integration of various tools and technologies studied in the course
    Presentation and documentation of the project

    11. Emerging Trends in Big Data

    Machine learning and AI in Big Data
    Edge computing
    Graph databases and analytics
    Continuous evolution and future directions


    Please Visit AWS Official Site: || Locus Academy ha s more than a decade experience in delivering the training/staffing on Big Data Engineering with Data Modeling and Architecture for corporates across the globe. The participants for the training/staffing on Big Data Engineering with Data Modeling and Architecture are extremely satisfied and are able to implement the learnings in their on going projects.

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