Data Collection Frameworks for Data Professionals


Data Collection Frameworks for Data Professionals , Learn all about the Data Collection Frameworks and become a master Data professional.

What you”ll learn:

  • Understanding Data Collection Principles
  • Exploring Data Collection Methods and Tools
  • Ensuring Data Quality and Integrity
  • Designing Effective Data Collection Strategies


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:

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. Module 7: Observability Frameworks
    • Introduction to Prometheus for monitoring and alerting
    • Creating interactive dashboards with Grafana
    • Best practices for achieving comprehensive system observability
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