Java for Data-Driven Applications

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Course Content

UNIT 1: Foundations of Data-Driven Application Design
Objective: Understand data-centric software systems.

  • What are data-driven applications
  • Types of data: structured, semi-structured, unstructured
  • Data lifecycle: ingestion → processing → storage → analysis → reporting
  • Role of Java in data-intensive systems
  • Batch vs real-time data processing
  • Data quality, consistency, and integrity
  • Overview of analytics and reporting systems

UNIT 2: Data Modeling & Java Application Architecture
Objective: Design applications where data drives logic.

UNIT 3: Advanced Java Collections for Data Processing
Objective: Use Java Collections to manage large datasets.

UNIT 4: File-Based Data Processing in Java
Objective: Handle enterprise data files.

UNIT 5: Java Streams API for Data Analytics
Objective: Perform analytics using modern Java features.

UNIT 6: Database-Driven Data Processing (JDBC Advanced)
Objective: Build database-centric data pipelines.

UNIT 7: Data Validation, Transformation & Business Rules
Objective: Ensure data correctness and usability.

UNIT 8: Multithreading & Performance in Data Applications
Objective: Optimize data-heavy Java programs.

UNIT 9: Reporting & Visualization Using Java
Objective: Convert data into insights.

UNIT 10: Data Security & Compliance
Objective: Secure data-driven systems.

UNIT 11: Testing & Quality Assurance for Data Systems
Objective: Validate correctness and reliability.

UNIT 12: Industry Case Studies (Data-Centric Systems)
Objective: Learn from real-world examples.

UNIT 13: Capstone Project – Data-Driven Java System
Objective: Deliver an industry-grade data application.

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