Oracle Health Technical Solution Analyst II - Support

Oracle

Let's explore some common data structures and algorithms. I'd like you to describe the following: Arrays: Explain what an array is and how it stores data. What are the advantages and disadvantages of using arrays? Provide an example of how you would use an array in a real-world scenario. For instance, how could you use an array to store a list of student names or inventory items? Linked Lists: What is a linked list, and how does it differ from an array? Describe the different types of linked lists (singly, doubly, circular). Walk me through the process of inserting a node into a singly linked list. What are the time complexities of insertion and deletion in a linked list? Stacks and Queues: Explain the concepts of stacks and queues. What are the key differences between them? (LIFO vs FIFO). Give an example of a situation where you would prefer to use a stack over a queue, and vice versa. How could you implement a queue using two stacks? Trees: Describe what a tree data structure is. What are the different types of trees (binary tree, binary search tree, etc.)? Explain the properties of a binary search tree. How does it enable efficient searching? How would you traverse a binary tree (in-order, pre-order, post-order)? Provide examples. Sorting Algorithms: Explain the concept of sorting algorithms. Describe the following sorting algorithms: Bubble Sort, Insertion Sort, Merge Sort, and Quick Sort. What are the time complexities of each of these sorting algorithms in the best, average, and worst-case scenarios? Which sorting algorithm would you choose for a nearly sorted array, and why? Searching Algorithms: Describe the difference between linear search and binary search. When is binary search applicable, and what are its advantages? What is the time complexity of linear search and binary search? For each of these, please be prepared to discuss their real-world applications, time and space complexities, and trade-offs.

Oracle

Let's design a system for deleting all user data in a large-scale application. Consider the following requirements: Compliance: The system must adhere to data privacy regulations (e.g., GDPR, CCPA) regarding the right to be forgotten. This means all personal data must be permanently and irrevocably deleted. Data Scope: User data is distributed across various databases (e.g., relational, NoSQL), object storage, and potentially third-party services. Examples include: User profiles in a relational database (name, email, address). User-generated content (photos, videos) in object storage. User activity logs in a NoSQL database. User data cached in a Redis cluster. User accounts on integrated third-party services (e.g., payment processors, social media platforms). Performance: The deletion process should be efficient and not significantly impact the performance of other system operations. Consider the impact on databases and other services during peak hours. Consistency: The system must ensure data consistency. For example, if a user has dependencies on other data (e.g., a user is an administrator of a group), these dependencies must be handled correctly (e.g., reassigning ownership, deleting dependent data). Auditability: All deletion requests and actions must be logged for auditing and compliance purposes. The logs should record who requested the deletion, when it was requested, what data was deleted, and the outcome of the deletion process. Error Handling: The system should gracefully handle errors and retries. If a deletion fails in one component, it should be retried or rolled back appropriately, and alerts should be generated. Scalability: The system must be able to handle a large number of deletion requests concurrently. Data Minimization: Before initiating the deletion process, verify if data minimization techniques can be applied instead of complete deletion, such as anonymization or pseudonymization, especially for datasets needed for analytical purposes. Given these requirements, how would you design a system to handle user data deletion requests? Discuss the architecture, components, data flow, and any trade-offs you would consider.

Oracle

Let's delve into your professional background. I'm interested in understanding the scope and impact of your previous experiences and projects. To begin, walk me through your resume, highlighting the roles and projects that you believe best showcase your skills and abilities relevant to this position. For each experience, please elaborate on the following aspects: Your responsibilities: What were your primary duties and tasks in each role? Technical skills utilized: Which programming languages, tools, and technologies did you employ? Project outcomes: What were the results or deliverables of your projects? Did you achieve specific goals or metrics? Challenges and solutions: Describe any significant challenges you faced and how you overcame them. What innovative solutions did you implement? Teamwork and collaboration: How did you collaborate with your team members and stakeholders to achieve project objectives? Furthermore, I'd like to hear about any personal projects or open-source contributions that demonstrate your passion for software development. Please provide specific examples that illustrate your problem-solving skills, coding proficiency, and commitment to continuous learning. Finally, are there any gaps in your resume that require further clarification? I want to get a thorough understanding of your professional journey and how it has prepared you for this opportunity.