Course curriculum

    1. Course overview: Mastering Data Integration: Design, Development, and Best Practices with Modern Trends

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    2. Slide Mastering Data Integration: Design, Development, and Best Practices with Modern Trends

    1. 1.0 Introduction to Data Integration

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    2. 1.1 What is data integration

    3. 1.2 Challenges, benefits and Business use cases for data integration

    4. 1.3 Introduction to data integration Architectures and Business Intelligence (BI)

    1. 2.1 Defining data integration requirements

    2. 2.2 The Source system analysis and profiling

    3. 2.3 Data quality assessment and cleansing techniques

    4. 2.4 Data volume analysis and target system mapping

    5. 2.5 Introduction to data integration modeling concepts

    1. 3.0 Overview about Data Integration Design

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    2. 3.1 Macro design best practices: Source system selection and prioritization

    3. 3.2 Macro design best practices: Data transformation strategies

    4. 3.3 Macro design best practices: Target system design considerations

    5. 3.4 Micro design best practices: Component-based design principles

    6. 3.5 Micro design best practices: Physical data integration modeling techniques

    7. 3.6 Micro design best practices: Coding standards and documentation practices

    8. 3.7 Micro design best practices: Data security and access control considerations

    1. 4.0 Overview about Data Integration Development

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    2. 4.1 Data extraction techniques (full vs. incremental loads)

    3. 4.2 Change data capture (CDC) methods

    4. 4.3 Error handling and data integrity checks

    5. 4.4 Data transformation and cleansing in development environments

    6. 4.5 Unit testing and integration testing strategies for data integration processes

    1. 5.0 Overview about Data Integration Deployment and Management

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    2. 5.1 Building and deploying data integration pipelines

    3. 5.2 Continuous integration and continuous delivery (CI/CD) for data integration

    4. 5.3 Data integration monitoring and performance optimization techniques

    5. 5.4 Production support considerations and troubleshooting procedures

About this course

  • $19.00
  • 39 lessons
  • 3 hours of video content

Mastering Data Integration Patterns

Mastering Data Integration: Design, Development and Management

📚 What You'll Learn

  • 🔑 Fundamentals of Data Integration: Understand core principles and applications in business intelligence.
  • 📐 Analyze and Design Architectures: Master the process of creating effective data integration architectures and models.
  • ⚙️ Develop Data Integration Pipelines: Build robust pipelines using best practices for data extraction, transformation, and loading (ETL).
  • 🚀 Deploy and Manage Solutions: Apply CI/CD and other modern deployment practices to maintain data integration solutions.
  • 📊 Tackle Advanced Challenges: Address real-time and big data integration challenges effectively.
  • ☁️ Stay Current with Emerging Trends: Explore the latest in cloud-based platforms and governance techniques.

📋 Requirements

  • 💻 Basic Understanding of Databases and SQL
  • 📊 Familiarity with Data Management Concepts (Preferred)
  • 📈 Knowledge of Business Intelligence (BI) Concepts (Preferred)
  • 🔧 Exposure to ETL Tools and Technologies (Optional)
  • ☁️ Basic Understanding of Cloud Computing (Optional)

📝 Description

This six-module course covers data integration from foundational concepts to advanced techniques, empowering you to build data solutions that enhance business intelligence and maximize the value of your data assets.

Course Modules:

Module 1: Introduction to Data Integration
Gain an understanding of data integration essentials, including architectures like ETL, ELT, and Data Vault, and the connection between data integration and BI.

Module 2: Data Integration Analysis
Analyze your data landscape to define integration requirements, assess data quality, and understand target system mapping.

Module 3: Data Integration Design
Learn best practices for designing robust data integration solutions, from source system selection to security and access controls.

Module 4: Data Integration Development
Transform designs into action with techniques for data extraction, change data capture (CDC), and integrity checks, along with testing strategies.

Module 5: Data Integration Deployment and Management
Explore sustainable deployment, with a focus on CI/CD, monitoring, and performance optimization for data integration pipelines.

Module 6: Advanced Data Integration Topics with Modern Trends
Dive into real-time and big data integration challenges, cloud-based platforms, and emerging trends in data governance and metadata management.

👥 Who This Course Is For

  • 📊 Data Professionals (Data Analysts, Data Engineers) seeking to deepen integration process knowledge.
  • 💼 IT Professionals involved in managing or implementing data systems.
  • 👩‍💻 Developers and Engineers looking to enhance their skills in ETL processes and data management.
  • 📈 Business Intelligence Professionals wanting to understand how integrated data supports BI systems.
  • 🏢 Professionals aiming to build or improve data integration solutions within their organization.

Discover your potential, starting today

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