Data Collection Frameworks for Data Professionals
KultureHire Education
42:36
Description
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
Who is this for?
What You Need to Know?
More details
DescriptionThis 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
Who this course is for:
- Data Analysts looking to learn how to effectively collect and manage data for analysis purposes.
- Business Managers looking to understand how data collection impacts decision-making and organizational success
- IT Professionals who are looking to learn about integrating and optimizing data collection within existing IT infrastructure.
- Market Researchers who want to explore techniques for collecting relevant and actionable market data
- Entrepreneurs who wants to acquire skills to gather and leverage data for business growth and innovation
- Students who want to build a strong understanding of data collection frameworks as a basis for future roles or academic pursuits
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
Who this course is for:
- Data Analysts looking to learn how to effectively collect and manage data for analysis purposes.
- Business Managers looking to understand how data collection impacts decision-making and organizational success
- IT Professionals who are looking to learn about integrating and optimizing data collection within existing IT infrastructure.
- Market Researchers who want to explore techniques for collecting relevant and actionable market data
- Entrepreneurs who wants to acquire skills to gather and leverage data for business growth and innovation
- Students who want to build a strong understanding of data collection frameworks as a basis for future roles or academic pursuits
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KultureHire Education
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Udemy
View courses Udemy- language english
- Training sessions 11
- duration 42:36
- Release Date 2024/05/17