Data Collection Frameworks For Data Professionals

What you'll learn
Understanding Data Collection Principles
Exploring Data Collection Methods and Tools
Ensuring Data Quality and Integrity
Designing Effective Data Collection Strategies
Requirements
No Prerequisite as such
Description
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 AnalyticsOverview of CRISP-DM and TDSP frameworksUnderstanding the data lifecycle and key data processing stagesPractical applications and case studiesModule 2: Web and Mobile AnalyticsIn-depth exploration of Google Analytics and Adobe AnalyticsHands-on exercises for user behavior tracking and conversion analysisImplementing analytics strategies for web and mobile applicationsModule 3: User Engagement AnalyticsUtilizing Mixpanel and Amplitude for user engagement analysisA/B testing and cohort analysis techniquesDeveloping data-driven strategies for user retentionModule 4: Centralized Logging and MonitoringImplementation of ELK Stack for centralized loggingReal-time log analysis using SplunkBuilding custom dashboards for effective monitoringModule 5: Real-Time Data Streaming FrameworksApache Kafka and its role in building data pipelinesReal-world applications of Apache Flink in stream processingDesigning scalable and fault-tolerant streaming architecturesModule 6: Cloud-Based Data CollectionAWS Kinesis and Google Cloud Pub/Sub for cloud-based data streamingScalability considerations in cloud-based data solutionsIntegration with other cloud services for end-to-end data processingModule 7: Observability FrameworksIntroduction to Prometheus for monitoring and alertingCreating interactive dashboards with GrafanaBest practices for achieving comprehensive system observability
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Where and why we need data collection
Section 2: Types and Frameworks of Data Collection
Lecture 3 Types of Data Collection
Lecture 4 Mobile and Web Analytics Framework
Lecture 5 User Engagement Analytics Frameworks
Lecture 6 Centralized Logging Frameworks
Lecture 7 Real time Data Streaming Frameworks
Lecture 8 Cloud-Based Data Collection Frameworks
Lecture 9 Observability Frameworks
Section 3: Business Context and Tools for Data Collection
Lecture 10 Business Evolution and Frameworks at different stages of the business
Lecture 11 Tools for Data Collection Frameworks
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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