Imagine you are tasked with designing a database system for a large e-commerce platform. The platform sells various products to customers worldwide and handles a high volume of transactions daily. Your goal is to design a robust and efficient database schema that can support the platform's operations, provide insightful analytics, and ensure data integrity.

a) Database Design:

1. Describe the steps you would take to design the initial database schema for the e-commerce platform. What considerations would you keep in mind during the design phase?
2. Identify and define the entities and relationships that are relevant to the e-commerce domain. How would you represent these entities in the database schema?
3. Explain the process of normalization and its importance in database design. How would you apply normalization techniques to ensure the integrity and efficiency of the database schema?
4. Discuss the factors that influence the choice between a relational database management system (RDBMS) and a NoSQL database for this e-commerce platform. Based on the requirements, justify your decision regarding the type of database system to use.

b) Performance Optimization:

1. Outline the strategies you would employ to optimize the performance of the database system, considering the high volume of transactions and data access patterns.
2. Explain the role of indexing in database performance optimization. Which columns would you consider indexing, and why?
3. Describe the concept of database partitioning and its relevance to scalability and performance. How would you implement database partitioning in the context of the e-commerce platform?
4. Discuss the importance of query optimization techniques such as query rewriting, query caching, and using appropriate join strategies. Provide examples of scenarios where these techniques would be beneficial.

c) Data Integrity and Security:

1. Outline the measures you would implement to ensure data integrity within the database system. How would you enforce constraints and validations to prevent data inconsistencies?
2. Discuss the importance of data encryption and access control mechanisms in safeguarding sensitive information stored in the database. What encryption techniques would you use, and how would you manage user privileges and roles?
3. Explain the concept of database auditing and logging. What events and activities would you monitor, and how would you ensure compliance with regulatory requirements such as GDPR or PCI DSS?

d) Scalability and High Availability:

1. Describe the strategies you would employ to ensure the scalability of the database system to handle increasing loads and growing data volumes over time.
2. Discuss the concept of database replication and its role in achieving high availability and fault tolerance. How would you design a replication strategy for the e-commerce platform?
3. Explain the use of sharding or partitioning techniques to distribute data across multiple servers or clusters. What considerations would you take into account when implementing sharding?

e) Data Analytics and Reporting:

1. Outline the approach you would take to enable data analytics and reporting capabilities within the database system. What tools and technologies would you leverage for data analysis and visualization?
2. Discuss the design of dimensional models such as star schemas or snowflake schemas for supporting analytical queries and reporting requirements. How would you populate and maintain these dimensional models?
3. Describe the process of Extract, Transform, Load (ETL) and its importance in integrating data from various sources into the database system. How would you design and implement an ETL pipeline for the e-commerce platform?

f) Disaster Recovery and Backup:

1. Explain the importance of implementing a robust disaster recovery and backup strategy for the database system. What measures would you take to ensure data durability and recovery in the event of system failures or disasters?
2. Discuss the different types of database backups, including full backups, incremental backups, and differential backups. How would you schedule and manage these backups to minimize data loss and downtime?