What does the the Modern Data Platform course cover?
the Modern Data Platform is covered here in 10 modules: Introduction to Modern Data Platforms: Defining modern data platforms, Data Storage and Management: Data warehousing and ETL, Data governance and quality, Data Processing and Analytics: Machine learning and AI, Data analytics and visualization and 7 more.
How do you approach the Modern Data Platform step by step?
The work is sequenced in 10 stages. It starts with Introduction to Modern Data Platforms: Defining modern data platforms, moves through Data Storage and Management: Data warehousing and ETL, Data governance and quality and Data Processing and Analytics: Machine learning and AI, Data analytics and visualization, and ends at Case Studies and Real-World Applications: Future directions and trends.
What is in Module 1 of the the Modern Data Platform course?
Module 1 is Introduction to Modern Data Platforms: Defining modern data platforms. It works through defining modern data platforms, key characteristics and benefits, overview of data infrastructure components and 1 more. It sets the vocabulary the remaining 9 modules build on.
How is the the Modern Data Platform course delivered?
The the Modern Data Platform course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.
How much does the the Modern Data Platform course cost?
The the Modern Data Platform course is $199 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.
Closely related courses: Infrastructure Platform Toolkit, Platform Infrastructure and Platform Business Model Kit, Cloud Platform in Infrastructure Provider Kit, Deployment Platform in Infrastructure Deployment Kit.
More answers: what you get with every course, refund policy, all help answers.
Mastering the Modern Data Platform: A Comprehensive Guide to Building and Managing a Secure and Scalable Data Infrastructure
Course Overview
This comprehensive course is designed to equip participants with the skills and knowledge needed to build and manage a secure and scalable data infrastructure. Participants will receive a certificate upon completion, issued by The Art of Service.Course Features
- Interactive and engaging learning experience
- Comprehensive and up-to-date curriculum
- Personalized learning experience
- Practical and real-world applications
- High-quality content and expert instructors
- Certificate upon completion
- Flexible learning options
- User-friendly and mobile-accessible platform
- Community-driven and interactive discussion forums
- Actionable insights and hands-on projects
- Bite-sized lessons and lifetime access
- Gamification and progress tracking
Course Outline
Module 1. Introduction to Modern Data Platforms: Defining modern data platforms
- Defining modern data platforms
- Key characteristics and benefits
- Overview of data infrastructure components
- Importance of security and scalability
Module 2. Data Storage and Management: Data warehousing and ETL, Data governance and quality
- Overview of data storage options (relational, NoSQL, cloud-based)
- Data modeling and schema design
- Data warehousing and ETL
- Data governance and quality
Module 3. Data Processing and Analytics: Machine learning and AI, Data analytics and visualization
- Overview of data processing options (batch, real-time, streaming)
- Data integration and interoperability
- Data analytics and visualization
- Machine learning and AI
Module 4. Data Security and Compliance: Identity and access management
- Overview of data security threats and risks
- Data encryption and access control
- Identity and access management
- Compliance and regulatory requirements
Module 5. Data Scalability and Performance: Data caching and optimization
- Overview of data scalability options (horizontal, vertical)
- Data partitioning and sharding
- Data caching and optimization
- Performance monitoring and tuning
Module 6. Cloud-Based Data Platforms: Overview of (AWS, Azure, GCP), Cloud-based data storage options
- Overview of cloud-based data platforms (AWS, Azure, GCP)
- Cloud-based data storage options
- Cloud-based data processing options
- Cloud-based data security and compliance
Module 7. Data Architecture and Design: Data architecture implementation
- Overview of data architecture patterns
- Data architecture design principles
- Data architecture implementation
- Data architecture best practices
Module 8. Data Engineering and Operations: Data quality and integrity, Data operations and maintenance
- Overview of data engineering tasks and responsibilities
- Data pipeline design and implementation
- Data quality and integrity
- Data operations and maintenance
Module 9. Data Science and Machine Learning: Data science best practices
- Overview of data science tasks and responsibilities
- Machine learning algorithms and techniques
- Data visualization and communication
- Data science best practices
Module 10. Case Studies and Real-World Applications: Future directions and trends
- Real-world examples of modern data platforms
- Case studies of successful data infrastructure implementations
- Lessons learned and best practices
- Future directions and trends