NBA Data Pipeline

NBA Player Stats

ID	Name	Position	Team	Abbreviation
${player.id}	${player.fullName}	${player.position}	${player.team}	${player.abbreviation}

`; dataContainer.innerHTML = tableHTML; } document.addEventListener('DOMContentLoaded', async () => { // Check if data is already in local storage const localData = loadDataLocally(); if (localData) { console.log('Data loaded from local storage.'); displayData(localData); } else { console.log('Fetching data from API...'); const rawData = await fetchData(); const transformedData = transformData(rawData); storeDataLocally(transformedData); // Store data in local storage displayData(transformedData); } }); // Security Considerations for a Real-World Data Pipeline (Beyond Browser Limitations): // -------------------------------------------------------------------------------- // 1. Data Storage: // - For persistent and scalable storage, cloud databases (PostgreSQL, BigQuery, AWS S3) are essential. // - Data should be stored securely, considering encryption at rest and proper database configurations. // // 2. Encryption: // - Data in transit is secured via HTTPS when fetching from the API. // - For data at rest in a real database, database-level encryption features should be enabled. // // 3. IAM Roles and Access Control: // - Implement Identity and Access Management (IAM) roles to control access to the database and data pipeline components. // - Grant least privilege access, ensuring only authorized users and services can access specific data or perform actions. // // 4. Continuous Monitoring and Security Policy Enforcement (Jit Integration): // - In a cloud environment, integrate with security monitoring tools and services (like Jit) to: // - Detect misconfigurations in the data pipeline infrastructure. // - Monitor for security policy violations and unauthorized access attempts. // - Automate security checks and compliance monitoring. // // 5. Data Transformation and Cleaning: // - Implement robust data validation and sanitization processes during the transformation step to prevent data integrity issues and security vulnerabilities (e.g., injection attacks if data is used in queries). // // Note: This browser-based example uses local storage for demonstration purposes, which is not suitable for production data pipelines // due to security and scalability limitations. A real-world pipeline would require server-side components, a proper database, // and comprehensive security measures as outlined above. ```