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Course Outline
Foundations of Data Platforms
- Definition of databases, data platforms, and big data systems.
- Types of data: structured, semi-structured, and unstructured.
- Primary business drivers for adopting modern data solutions.
- Key characteristics and essential terminology of big data.
Database Fundamentals
- Core relational database concepts: tables, rows, columns, and keys.
- Utilization of SQL for data retrieval and management.
- Introduction to data modeling and basic schema design.
- Practical aspects of transactions, consistency, and reliability.
Selecting Between Relational and NoSQL Systems
- Comparison of relational databases versus NoSQL databases.
- Overview of document, key-value, column, and graph data models.
- Strengths, limitations, and trade-offs associated with each approach.
- Aligning database selections with specific business requirements.
Data Warehousing and Big Data Processing
- Roles of data warehouses, data lakes, and lakehouse architectures.
- ETL and ELT concepts for data extraction, transformation, and loading.
- Concepts of batch and stream processing.
- High-level perspective on distributed storage and processing.
Governance, Security, and Data Quality
- Fundamental governance principles, including ownership and stewardship.
- Considerations for access control, privacy, and security.
- Common data quality issues and practical strategies for improvement.
- Compliance and ethical data usage in business contexts.
Practical Applications and Course Conclusion
- Typical use cases in reporting, analytics, and operational systems.
- Review of example architectures for various scenarios.
- Common implementation challenges and risk mitigation strategies.
- Summary, recommendations, and guidance for further learning.
Requirements
- A fundamental understanding of data, reporting, and standard business information workflows.
- Experience utilizing spreadsheets, reports, or business applications that handle data.
- Basic background in technical, analytical, or business systems.
Target Audience
- Business analysts and reporting specialists.
- IT personnel, developers, and system support staff.
- Managers and decision-makers involved in data-centric projects.
14 Hours
Testimonials (2)
The training instruments provided.
- UNIFI
Course - NoSQL Database with Microsoft Azure Cosmos DB
Hands on exercises. Class should have been 5 days, but the 3 days helped to clear up a lot of questions that I had from working with NiFi already
