Google Cloud Digital LeaderDigital transformation with Google CloudHard
A healthcare provider is undertaking a digital transformation to improve patient outcomes and operational efficiency. They need to analyze anonymized patient data, medical imaging, and genomics information to develop personalized treatment plans and predict disease outbreaks. The solution requires secure storage for sensitive data, powerful analytical capabilities, and integration with advanced machine learning for pattern recognition. Which combination of Google Cloud services would best meet these needs?
- ACloud SQL, Cloud CDN, App Engine
- BCompute Engine, Cloud Spanner, Cloud Pub/Sub
- CCloud Storage, BigQuery, Vertex AI
- DCloud Functions, Firebase, Cloud IoT Core
Show answer & explanationAnswer & explanation
Correct answer: C. Cloud Storage, BigQuery, Vertex AI
Cloud Storage provides secure, scalable storage for diverse data types including medical images and genomics. BigQuery offers powerful analytical capabilities for petabyte-scale data, and Vertex AI provides a comprehensive platform for building, deploying, and managing machine learning models, which is crucial for personalized treatment plans and disease prediction.
Why the other options are wrong
- A. Cloud SQL for transactional data, Cloud CDN for content delivery, and App Engine for web apps are not the primary tools for large-scale secure data storage and advanced ML analytics.
- B. Compute Engine for VMs, Cloud Spanner for globally consistent transactions, and Cloud Pub/Sub for messaging are not optimized for the described analytical and ML workflow with medical data.
- D. Cloud Functions for serverless execution, Firebase for mobile/web app development, and Cloud IoT Core for IoT device management are not the core services for advanced medical data analytics and ML.
Healthcare Data Analytics on Google Cloud
Leveraging Google Cloud services for secure storage, powerful analytics, and machine learning on sensitive healthcare data to improve patient outcomes.
- Requires robust security and compliance (HIPAA).
- Handles diverse data types: structured, unstructured, imaging, genomics.
- Utilizes ML for predictive analytics and personalized medicine.
Memory trick: Storage for the records, BigQuery for insights, Vertex AI for the future.