01 Data Concepts

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# Course Outline: Data Concepts

This course on Data Concepts aims to provide a comprehensive understanding of fundamental data principles and concepts while integrating specific certifications and technologies such as Microsoft DP-900, Microsoft AZ-900, indexes, SQL automation, and relational database design. The course is structured to accommodate a broad audience, from beginners to intermediate learners, and primes students for industry-recognized certifications.

Course Objectives

• Understand core data concepts and their applications.
• Gain foundational knowledge of Microsoft DP-900 and Microsoft AZ-900.
• Explore the use of indexes in databases.
• Learn SQL automation techniques.
• Understand the principles of relational database design.

Course Modules

Module 1: Introduction to Data Concepts

• Overview of Data Concepts

- Definition and importance of data

- Types of data: structured, unstructured, and semi-structured

• Core Data Concepts in Business

- The role of data in decision-making

- Data lifecycle and governance

Module 2: Microsoft DP-900: Azure Data Fundamentals

• Introduction to Microsoft DP-900

- Overview of the certification

- Benefits and career opportunities

• Core Data Concepts in Azure

- Relational, non-relational, big data, and data analytics

- Data visualization and reporting

• Azure Data Services

- Azure SQL, Cosmos DB

- Data Lake and Synapse Analytics

Module 3: Microsoft AZ-900: Azure Fundamentals

• Introduction to Microsoft AZ-900

- Overview of the certification

- Benefits and career opportunities

• Azure Core Services

- Virtual machines, networks, and storage

• Security, Privacy, Compliance, and Trust

- Security features in Azure

- Compliance and privacy principles

• Azure Pricing and Support

- Cost management and service level agreements

Module 4: Database Indexing

• Introduction to Indexes

- What are indexes?

- Importance and types of indexes

• Implementing Indexes in Databases

- Creating and managing indexes

- Performance optimization using indexes

• Challenges in Index Management

- Index maintenance and overhead

- Best practices in index usage

Module 5: SQL Automation

• Introduction to SQL Automation

- Benefits of automation in SQL

- Overview of SQL automation tools

• Scripting and Automation

- Writing scripts for automation

- Scheduling and executing automated tasks

• Automating Data Pipelines

- ETL process automation

- Monitoring and alerting mechanisms

Module 6: Relational Database Design

• Principles of Relational Database Design

- Normalization and denormalization

- Entity-relationship modeling

• Designing Effective Databases

- Key constraints and relationships

- Designing for performance and scalability

• Case Studies and Best Practices

- Real-world examples of effective database design

- Common pitfalls and how to avoid them