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Mastering Data Engineering for Marketing Technology

Mastering Data Engineering for Marketing Technology

$199.00
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Mastering Data Engineering for Marketing Technology



Course Overview

This comprehensive course is designed to equip marketing professionals with the skills and knowledge needed to master data engineering and drive business growth through data-driven decision making. Participants will receive a certificate upon completion, issued by The Art of Service.



Course Features

  • Interactive and engaging learning experience
  • Comprehensive curriculum covering 80+ topics
  • Personalized learning with expert instructors
  • Up-to-date and practical knowledge with real-world applications
  • High-quality content and hands-on projects
  • Certificate of Completion issued by The Art of Service
  • Flexible learning with lifetime access and mobile accessibility
  • Community-driven with gamification and progress tracking
  • Actionable insights and bite-sized lessons


Course Outline

Module 1: Introduction to Data Engineering

  • Defining data engineering and its role in marketing technology
  • Understanding the data engineering process
  • Key concepts and terminology
  • Case studies: successful data engineering projects

Module 2: Data Engineering Fundamentals

  • Data storage solutions: relational databases, NoSQL databases, and data warehouses
  • Data processing: batch processing, real-time processing, and stream processing
  • Data ingestion: APIs, data pipelines, and ETL tools
  • Data governance: data quality, data security, and data compliance

Module 3: Data Engineering for Marketing

  • Marketing data sources: customer data, social media data, and campaign data
  • Data engineering for marketing analytics: metrics, KPIs, and data visualization
  • Data engineering for marketing automation: workflows, triggers, and actions
  • Case studies: data engineering for marketing success stories

Module 4: Data Engineering Tools and Technologies

  • Apache Hadoop and Spark: big data processing and analytics
  • Apache Kafka and Flume: data ingestion and streaming
  • Apache Beam and Airflow: data processing and workflow management
  • Cloud-based data engineering tools: AWS, GCP, and Azure

Module 5: Data Engineering Best Practices

  • Data engineering design patterns: data lakes, data marts, and data vaults
  • Data engineering security best practices: authentication, authorization, and encryption
  • Data engineering performance optimization: data partitioning, data caching, and data parallelism
  • Data engineering testing and validation: data quality, data integrity, and data accuracy

Module 6: Advanced Data Engineering Topics

  • Machine learning and AI in data engineering: predictive analytics and decision-making
  • Real-time data engineering: event-driven architecture and stream processing
  • Graph databases and knowledge graphs: data relationships and semantic search
  • Cloud-native data engineering: serverless computing and containerization

Module 7: Data Engineering Project Management

  • Data engineering project planning: goals, timelines, and resources
  • Data engineering project execution: agile methodologies and iterative development
  • Data engineering project monitoring and control: metrics, KPIs, and status reporting
  • Data engineering project closure: lessons learned and post-project review

Module 8: Data Engineering Career Development

  • Data engineering career paths: roles, responsibilities, and skills
  • Data engineering certifications: industry-recognized credentials and training programs
  • Data engineering networking: professional associations, conferences, and meetups
  • Data engineering continuing education: staying up-to-date with industry trends and advancements


Certificate of Completion

Upon completing the course, participants will receive a Certificate of Completion issued by The Art of Service. This certificate demonstrates expertise in data engineering for marketing technology and can be showcased on resumes, LinkedIn profiles, and other professional platforms.

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