1. Scalability for handling massive data volumes.

2. Real-time or near real-time processing for timely insights.

3. Handling diverse data types: structured, semi-structured, and unstructured.

4. Flexibility in data sources and formats for comprehensive analysis.

5. Utilization of advanced analytics techniques like machine learning.

6. Capability for real-time analytics on streaming data.

7. Cost-effectiveness through distributed computing technologies.

8. Data visualization for effective communication of insights.

9. Integration with existing systems for seamless operation.

10. Ensuring data governance, security, and compliance.

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