Azure Data Engineer Associate (DP-203)
1 Design and implement data storage
1-1 Design data storage solutions
1-1 1 Identify data storage requirements
1-1 2 Select appropriate storage types
1-1 3 Design data partitioning strategies
1-1 4 Design data lifecycle management
1-1 5 Design data retention policies
1-2 Implement data storage solutions
1-2 1 Create and configure storage accounts
1-2 2 Implement data partitioning
1-2 3 Implement data lifecycle management
1-2 4 Implement data retention policies
1-2 5 Implement data encryption
2 Design and implement data processing
2-1 Design data processing solutions
2-1 1 Identify data processing requirements
2-1 2 Select appropriate data processing technologies
2-1 3 Design data ingestion strategies
2-1 4 Design data transformation strategies
2-1 5 Design data integration strategies
2-2 Implement data processing solutions
2-2 1 Implement data ingestion
2-2 2 Implement data transformation
2-2 3 Implement data integration
2-2 4 Implement data orchestration
2-2 5 Implement data quality management
3 Design and implement data security
3-1 Design data security solutions
3-1 1 Identify data security requirements
3-1 2 Design data access controls
3-1 3 Design data encryption strategies
3-1 4 Design data masking strategies
3-1 5 Design data auditing strategies
3-2 Implement data security solutions
3-2 1 Implement data access controls
3-2 2 Implement data encryption
3-2 3 Implement data masking
3-2 4 Implement data auditing
3-2 5 Implement data compliance
4 Design and implement data analytics
4-1 Design data analytics solutions
4-1 1 Identify data analytics requirements
4-1 2 Select appropriate data analytics technologies
4-1 3 Design data visualization strategies
4-1 4 Design data reporting strategies
4-1 5 Design data exploration strategies
4-2 Implement data analytics solutions
4-2 1 Implement data visualization
4-2 2 Implement data reporting
4-2 3 Implement data exploration
4-2 4 Implement data analysis
4-2 5 Implement data insights
5 Monitor and optimize data solutions
5-1 Monitor data solutions
5-1 1 Identify monitoring requirements
5-1 2 Implement monitoring tools
5-1 3 Analyze monitoring data
5-1 4 Implement alerting mechanisms
5-1 5 Implement logging and auditing
5-2 Optimize data solutions
5-2 1 Identify optimization opportunities
5-2 2 Implement performance tuning
5-2 3 Implement cost optimization
5-2 4 Implement scalability improvements
5-2 5 Implement reliability improvements
Implement Logging and Auditing

Implement Logging and Auditing

Key Concepts

Logging

Logging involves recording events and activities within a system to provide a chronological record of actions. This helps in troubleshooting, performance analysis, and understanding system behavior. Azure provides tools like Azure Monitor and Azure Log Analytics for comprehensive logging.

Example: A retail company might log all transactions processed by its e-commerce platform. These logs can be used to trace issues, analyze sales patterns, and ensure data integrity.

Analogy: Think of logging as keeping a diary of your daily activities. Each entry (log) records what you did, when you did it, and any outcomes, providing a detailed history that can be referenced later.

Auditing

Auditing involves systematically reviewing and verifying the integrity and compliance of system activities. This ensures that operations adhere to organizational policies and regulatory requirements. Azure provides tools like Azure Audit Logs and Azure Policy for auditing.

Example: A financial institution might audit access to sensitive customer data to ensure that only authorized personnel can view or modify the data.

Analogy: Consider auditing as a quality control process in a factory. Inspectors (auditors) check the production line (system activities) to ensure that all products (operations) meet the required standards (policies and regulations).

Log Management

Log management involves collecting, storing, analyzing, and archiving logs to ensure they are accessible and useful for future reference. This includes setting retention policies and ensuring log data is secure. Azure provides tools like Azure Log Analytics and Azure Storage for log management.

Example: A healthcare provider might manage logs by storing them in Azure Storage with a retention policy of 10 years, ensuring compliance with healthcare regulations.

Analogy: Think of log management as organizing a library. You need to catalog (collect), store (archive), and make books (logs) easily accessible for readers (analysts) while ensuring they are protected (secure).

Compliance and Regulatory Requirements

Compliance and regulatory requirements involve adhering to laws, regulations, and standards that govern data handling and security. This includes ensuring that logging and auditing practices meet legal and industry standards. Azure provides tools like Azure Compliance Manager and Azure Security Center to assist with compliance.

Example: A company operating in the European Union must comply with GDPR, which requires logging and auditing of data access and processing activities.

Analogy: Consider compliance and regulatory requirements as following the rules of a game. You need to understand and adhere to the rules (regulations) to participate and avoid penalties (fines).

Security and Incident Response

Security and incident response involve using logs and audit trails to detect, respond to, and mitigate security incidents. This includes setting up alerts for suspicious activities and conducting root cause analysis. Azure provides tools like Azure Security Center and Azure Sentinel for security and incident response.

Example: A cybersecurity team might use Azure Sentinel to monitor logs for signs of a potential data breach and initiate an incident response plan to address the threat.

Analogy: Think of security and incident response as having a fire alarm and fire brigade. The alarm (monitoring system) detects a fire (security incident), and the brigade (response team) quickly responds to extinguish the fire (mitigate the incident).