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Course Outline
Foundations of Data Platforms
- Definitions of databases, data platforms, and big data systems.
- Types of data: structured, semi-structured, and unstructured.
- Key business drivers behind modern data solutions.
- Characteristics of big data and essential terminology.
Database Fundamentals
- Relational database concepts, including tables, rows, columns, and keys.
- The use of SQL for data retrieval and management.
- Basic data modeling and simple schema design.
- Practical levels of transactions, consistency, and reliability.
Selecting Between Relational and NoSQL Systems
- Comparison of relational databases versus NoSQL databases.
- High-level overview of document, key-value, column, and graph models.
- Strengths, limitations, and tradeoffs of each approach.
- Aligning database choices with common business requirements.
Data Warehousing and Big Data Processing
- The purpose of data warehouses, data lakes, and lakehouse-style architectures.
- ETL (Extract, Transform, Load) and ELT concepts for data movement and preparation.
- Batch and stream processing concepts.
- A high-level perspective on distributed storage and processing.
Governance, Security, and Data Quality
- Core governance principles, ownership, and stewardship.
- Access control, privacy, and security considerations.
- Common data quality issues and practical improvement methods.
- Compliance and responsible data usage in business environments.
Practical Applications and Course Wrap-Up
- Typical use cases in reporting, analytics, and operational systems.
- Reviewing example architectures for various scenarios.
- Common implementation challenges and strategies to mitigate risk.
- Summary, recommendations, and next steps for further learning.
Requirements
- A foundational understanding of data, reports, and standard business information workflows.
- Practical experience using spreadsheets, reports, or business applications that interact with data.
- Basic background in technical, analytical, or business systems.
Audience
- Business analysts and reporting specialists.
- IT staff, developers, and system support personnel.
- Managers and decision-makers engaged 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
