Scenario: You are tasked with designing a scalable architecture for an e-commerce platform. How would you approach database design to ensure scalability and performance under high traffic loads?
- Denormalizing the database schema
- Implementing sharding
- Utilizing a single monolithic database
- Vertical scaling by adding more resources to existing servers
Sharding involves partitioning data across multiple database instances, allowing for horizontal scaling and distributing the workload evenly. It enables the system to handle increased traffic by spreading data and queries across multiple servers. This approach enhances scalability and performance by reducing the load on individual database servers.
Which of the following best describes a characteristic of NoSQL databases?
- Fixed schema
- Flexible schema
- Limited scalability
- Strong consistency
NoSQL databases typically offer a flexible schema, allowing for the storage of various types of data without the need to adhere to a rigid structure like in traditional relational databases.
What are the key considerations for choosing between batch loading and real-time loading strategies?
- Data complexity vs. storage requirements
- Data freshness vs. processing overhead
- Processing speed vs. data consistency
- Scalability vs. network latency
Choosing between batch loading and real-time loading involves weighing factors such as data freshness versus processing overhead. Batch loading may offer higher throughput but lower data freshness compared to real-time loading.
________ is a method of load balancing where incoming requests are distributed evenly across multiple servers to prevent overload.
- Content-based routing
- Least connections routing
- Round-robin routing
- Sticky session routing
Least connections routing is a load balancing technique that distributes incoming requests across multiple servers based on the current number of active connections. Servers with fewer connections receive more requests, helping to evenly distribute the workload and prevent any single server from becoming overwhelmed. This approach promotes efficient resource utilization and enhances system reliability by preventing overload on individual servers.
Scenario: A security breach occurs in your Data Lake, resulting in unauthorized access to sensitive data. How would you respond to this incident and what measures would you implement to prevent similar incidents in the future?
- Data Backup Procedures, Data Replication Techniques, Disaster Recovery Plan, Data Masking Techniques
- Data Normalization Techniques, Query Optimization, Data Compression Techniques, Database Monitoring Tools
- Data Validation Techniques, Data Masking Techniques, Data Anonymization, Data Privacy Policies
- Incident Response Plan, Data Encryption, Access Control Policies, Security Auditing
In response to a security breach in a Data Lake, an organization should enact its incident response plan, implement data encryption to protect sensitive data, enforce access control policies to limit unauthorized access, and conduct security auditing to identify vulnerabilities. Preventative measures may include regular data backups, disaster recovery plans, and data masking techniques to obfuscate sensitive information.
In data pipeline monitoring, ________ is the process of identifying and analyzing deviations from expected behavior.
- Anomaly detection
- Data aggregation
- Data transformation
- Data validation
Anomaly detection in data pipeline monitoring involves identifying and analyzing deviations from the expected behavior of the pipeline. This process often employs statistical techniques, machine learning algorithms, or predefined rules to detect unusual patterns or outliers in the data flow, which may indicate errors, bottlenecks, or data quality issues within the pipeline.
What is the main purpose of a wide-column store NoSQL database?
- Designed for transactional consistency
- Optimal for storing and querying large amounts of data
- Primarily used for key-value storage
- Suitable for highly interconnected data
A wide-column store NoSQL database is designed for efficiently storing and querying large volumes of data, typically organized in column families, making it optimal for analytical and big data workloads.
The process of transforming a logical data model into a physical implementation, including decisions about storage, indexing, and partitioning, is called ________.
- Data Normalization
- Data Warehousing
- Physical Design
- Query Optimization
The process described involves converting the logical representation of data into a physical implementation, considering various factors such as storage mechanisms, indexing strategies, and partitioning schemes.
What is the primary purpose of data lineage in metadata management?
- Encrypting sensitive data
- Optimizing database performance
- Storing backup copies of data
- Tracking the origin and transformation of data
Data lineage in metadata management primarily serves the purpose of tracking the origin, transformation, and movement of data throughout its lifecycle. It provides insights into how data is sourced, processed, and utilized across various systems and processes, facilitating data governance, compliance, and decision-making. Understanding data lineage helps organizations ensure data quality, lineage, and regulatory compliance.
The logical data model focuses on defining ________, attributes, and relationships between entities.
- Constraints
- Entities
- Tables
- Transactions
The logical data model focuses on defining entities, attributes, and relationships between entities, providing a structured representation of the data independent of any specific database technology or implementation.