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
Monitor and Optimize Data Solutions

Monitor and Optimize Data Solutions

Key Concepts

Performance Monitoring

Performance monitoring involves tracking the performance of data solutions to ensure they meet the required service levels. This includes monitoring metrics such as response time, throughput, and resource utilization. Azure provides tools like Azure Monitor and Application Insights for performance monitoring.

Example: A financial services company might use Azure Monitor to track the response time of its transaction processing system. If the response time exceeds a predefined threshold, alerts can be triggered to notify the operations team.

Analogy: Think of performance monitoring as checking the speedometer and fuel gauge of a car. You need to ensure the car is running efficiently and take action if it starts to slow down or run out of fuel.

Cost Management

Cost management involves tracking and optimizing the costs associated with data solutions. This includes monitoring resource usage, setting budgets, and optimizing resource allocation. Azure provides tools like Azure Cost Management and Azure Advisor for cost management.

Example: A retail company might use Azure Cost Management to track the costs of its data storage and processing resources. By analyzing usage patterns, the company can identify opportunities to reduce costs, such as resizing underutilized virtual machines.

Analogy: Consider cost management as managing a household budget. You need to track expenses, set limits, and find ways to save money without compromising on essential services.

Scalability and Load Balancing

Scalability and load balancing involve ensuring that data solutions can handle varying workloads by dynamically adjusting resource allocation. This includes scaling resources up or down based on demand and distributing workloads evenly across resources. Azure provides tools like Azure Kubernetes Service (AKS) and Azure Load Balancer for scalability and load balancing.

Example: An e-commerce platform might use Azure Kubernetes Service to automatically scale the number of application instances during peak shopping periods. Azure Load Balancer ensures that incoming traffic is distributed evenly across these instances.

Analogy: Think of scalability and load balancing as adjusting the number of lanes on a highway during rush hour. You need to add more lanes (scale up) to handle increased traffic and ensure that traffic is evenly distributed across all lanes (load balancing).

Data Quality Monitoring

Data quality monitoring involves tracking the accuracy, completeness, and consistency of data. This ensures that the data used for analytics is reliable and meets the required standards. Azure provides tools like Azure Data Catalog and Azure Data Quality Services for data quality monitoring.

Example: A healthcare provider might use Azure Data Quality Services to monitor the quality of patient records. By setting data quality rules, the provider can ensure that all records are complete, accurate, and consistent.

Analogy: Consider data quality monitoring as inspecting a product before it goes on sale. You check for defects, ensure it meets quality standards, and make necessary adjustments to ensure customer satisfaction.

Automation and Alerts

Automation and alerts involve setting up automated processes and notifications to respond to performance issues, cost anomalies, and data quality problems. This ensures timely intervention and reduces manual effort. Azure provides tools like Azure Logic Apps, Azure Functions, and Azure Monitor for automation and alerts.

Example: A marketing team might use Azure Logic Apps to automate the generation and delivery of weekly performance reports. Azure Monitor can be configured to send alerts if website traffic drops below a certain threshold.

Analogy: Think of automation and alerts as setting up a security system for your home. The system automatically detects intrusions (issues) and sends alerts (notifications) to ensure you can take immediate action.