Big Data & Internet Of Things (iot) Training Course: Integrate Iot Data

Introduction

Harness the power of interconnected devices with our Big Data and the Internet of Things (IoT) Training Course. This program is designed to equip you with the essential skills to integrate IoT data with Big Data platforms, enabling you to extract valuable insights from the vast streams of data generated by connected devices. In today's hyper-connected world, the ability to effectively manage and analyze IoT data is crucial for driving innovation and informed decisions. Our IoT training course provides hands-on experience and expert guidance, empowering you to build robust and scalable IoT data solutions.

This Big Data IoT training delves into the core concepts of IoT data integration, covering topics such as data ingestion, stream processing, and data analytics. You'll gain expertise in using industry-standard tools and techniques to integrate IoT data with Big Data platforms that meet the demands of modern data environments. Whether you're a data engineer, IoT developer, or data analyst, this Big Data and IoT course will empower you to build powerful IoT data applications.

Target Audience:

• Data Engineers
• IoT Developers
• Data Analysts
• Big Data Architects
• System Administrators
• Cloud Engineers
• Anyone needing IoT data integration skills

Course Objectives:

• Understand the fundamentals of Big Data and the Internet of Things (IoT).
• Master the integration of IoT data with Big Data platforms.
• Utilize data ingestion techniques for IoT data streams.
• Implement stream processing for real-time IoT data analysis.
• Design scalable and efficient IoT data architectures.
• Utilize cloud-based IoT and Big Data services.
• Troubleshoot and optimize IoT data pipelines.
• Implement data security and access control for IoT data.
• Integrate IoT data with analytics and visualization tools.
• Understand how to monitor and manage IoT data systems.
• Explore advanced IoT data processing techniques.
• Apply real world use cases for IoT data integration.
• Leverage machine learning for IoT data analysis.

Duration

10 Days

Course content

Module 1: Introduction to Big Data and IoT

• Fundamentals of Big Data and IoT.
• Overview of IoT data characteristics and challenges.
• Setting up an IoT data integration environment.
• Introduction to IoT and Big Data tools and frameworks.
• Best practices for IoT data integration.

Module 2: IoT Data Ingestion

• Utilizing message brokers (MQTT, Kafka) for IoT data ingestion.
• Implementing data ingestion from various IoT devices.
• Utilizing edge computing for data preprocessing.
• Implementing data serialization and deserialization.
• Best practices for data ingestion.

Module 3: Stream Processing for IoT Data

• Implementing stream processing engines (Flink, Spark Streaming).
• Utilizing real-time data analytics for IoT streams.
• Implementing data filtering and aggregation.
• Building real-time dashboards for IoT data.
• Best practices for stream processing.

Module 4: Scalable IoT Data Architectures

• Designing scalable IoT data architectures.
• Utilizing distributed data storage and processing.
• Implementing cloud-based IoT data solutions.
• Optimizing data pipelines for performance.
• Best practices for scalable architectures.

Module 5: Cloud-Based IoT and Big Data Services

• Utilizing AWS IoT and Big Data services.
• Utilizing Azure IoT and Big Data services.
• Utilizing Google Cloud IoT and Big Data services.
• Implementing serverless IoT data processing.
• Best practices for cloud services.

Module 6: Troubleshooting and Optimization

• Debugging IoT data pipelines.
• Analyzing data flow and performance.
• Utilizing monitoring tools and techniques.
• Optimizing data processing and storage.
• Best practices for troubleshooting.

Module 7: Data Security and Access Control

• Implementing data security for IoT data.
• Utilizing authentication and authorization.
• Implementing data encryption and masking.
• Implementing data auditing and compliance.
• Best practices for data security.

Module 8: Integration with Analytics and Visualization Tools

• Integrating IoT data with analytics tools (Tableau, Power BI).
• Utilizing data visualization for IoT data insights.
• Implementing interactive dashboards for IoT data.
• Best practices for analytics integration.

Module 9: Monitoring and Management

• Monitoring IoT data systems and pipelines.
• Implementing alerting and notifications.
• Utilizing monitoring tools and techniques.
• Managing IoT data infrastructure.
• Best practices for monitoring.

Module 10: Advanced IoT Data Processing

• Implementing time series analysis for IoT data.
• Utilizing geospatial data processing for IoT.
• Implementing complex event processing (CEP).
• Advanced techniques for IoT data analysis.
• Best practices for advanced processing.

Module 11: Real-World Use Cases

• Implementing IoT data for smart cities.
• Utilizing IoT data for industrial automation.
• Implementing IoT data for healthcare applications.
• Utilizing IoT data for environmental monitoring.
• Best practices for real world applications.

Module 12: Machine Learning for IoT Data

• Utilizing machine learning for IoT data analysis.
• Implementing anomaly detection for IoT data.
• Implementing predictive maintenance for IoT devices.
• Building machine learning models for IoT data.
• Best practices for machine learning.

Module 13: IoT Data on Cloud Platforms

• Deploying IoT data solutions on cloud platforms.
• Utilizing cloud-based IoT data services.
• Optimizing cloud resources for IoT data.
• Best practices for cloud deployment.

Module 14: IoT Data and Data Governance

• Implementing data governance policies for IoT data.
• Utilizing metadata management for IoT data.
• Implementing data lineage and data dictionary.
• Best practices for data governance.

Module 15: Future Trends in Big Data and IoT

• Emerging trends in IoT data integration.
• Utilizing AI and automation in IoT data workflows.
• Implementing edge computing for IoT data.
• Best practices for future IoT data.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.