Executive Development Programme in Streaming Data Innovation

• Streaming Data Architecture: Foundational concepts and best practices for building streaming data pipelines. This includes an overview of real-time data processing, data ingestion, and data storage technologies.
• Data Engineering for Streaming Platforms: Deep dive into designing, building, and maintaining data pipelines for real-time data processing, focusing on tools and techniques for data integration, transformation, and orchestration.
• Real-time Analytics with Streaming Data: Exploration of analytical techniques for streaming data, including data exploration, statistical analysis, and machine learning models for real-time prediction and decision making.
• Streaming Data Security and Compliance: Overview of security and compliance considerations for streaming data platforms, including data encryption, access controls, and regulatory requirements.
• Big Data and Streaming Data Integration: Strategies for integrating streaming data with big data platforms, including data warehouses and data lakes, for downstream analytics and reporting.
• Streaming Data Visualization and Dashboarding: Techniques for visualizing and presenting real-time data to stakeholders, including best practices for dashboard design and data storytelling.
• Machine Learning with Streaming Data: Hands-on exploration of machine learning techniques for streaming data, including supervised and unsupervised learning, online and offline models, and model evaluation.
• Streaming Data Governance and Operations: Overview of operational considerations for streaming data platforms, including data quality, data lineage, and incident management.