Data Collection Frameworks for Data Professionals

Learn all about the Data Collection Frameworks and become a master Data professional

This comprehensive course is designed for professionals seeking advanced knowledge and practical skills in leveraging cutting-edge data analytics and infrastructure frameworks. The course covers a range of topics, from web and mobile analytics to real-time data streaming and observability, providing participants with a solid foundation for designing and implementing robust data solutions.

Course Structure:

Module 1: Foundations of Data Analytics
- Overview of CRISP-DM and TDSP frameworks
- Understanding the data lifecycle and key data processing stages
- Practical applications and case studies
Module 2: Web and Mobile Analytics
- In-depth exploration of Google Analytics and Adobe Analytics
- Hands-on exercises for user behavior tracking and conversion analysis
- Implementing analytics strategies for web and mobile applications
Module 3: User Engagement Analytics
- Utilizing Mixpanel and Amplitude for user engagement analysis
- A/B testing and cohort analysis techniques
- Developing data-driven strategies for user retention
Module 4: Centralized Logging and Monitoring
- Implementation of ELK Stack for centralized logging
- Real-time log analysis using Splunk
- Building custom dashboards for effective monitoring
Module 5: Real-Time Data Streaming Frameworks
- Apache Kafka and its role in building data pipelines
- Real-world applications of Apache Flink in stream processing
- Designing scalable and fault-tolerant streaming architectures
Module 6: Cloud-Based Data Collection
- AWS Kinesis and Google Cloud Pub/Sub for cloud-based data streaming
- Scalability considerations in cloud-based data solutions
- Integration with other cloud services for end-to-end data processing
Module 7: Observability Frameworks
- Introduction to Prometheus for monitoring and alerting
- Creating interactive dashboards with Grafana
- Best practices for achieving comprehensive system observability