Which of the following is a key characteristic of distributed systems?

  • Centralized control
  • Fault tolerance
  • Low network latency
  • Monolithic architecture
Fault tolerance is a key characteristic of distributed systems, referring to their ability to continue operating despite individual component failures. Distributed systems are designed to handle failures gracefully by replicating data, employing redundancy, and implementing algorithms to detect and recover from faults without disrupting overall system functionality. This resilience ensures system availability and reliability in the face of failures, a crucial aspect of distributed computing.

Scenario: Your company is implementing a data warehouse to analyze sales data from multiple regions. As part of the design process, you need to determine the appropriate schema for the fact and dimension tables. Which schema would you most likely choose and why?

  • Bridge schema
  • Fact constellation schema
  • Snowflake schema
  • Star schema
In this scenario, a Star schema would be the most appropriate choice. It consists of one or more fact tables referencing any number of dimension tables, forming a star-like structure. This schema simplifies queries and ensures better performance due to denormalization, making it suitable for analytical purposes like analyzing sales data across multiple dimensions.

The process of preparing and organizing data for analysis in a Data Lake is known as ________.

  • Data Cleansing
  • Data Ingestion
  • Data Wrangling
  • ETL
Data Wrangling is the process of preparing and organizing raw data for analysis in a Data Lake. It involves cleaning, transforming, and structuring the data to make it suitable for various analytical tasks.

________ is a key principle of data governance frameworks, ensuring that data is accessible only to authorized users.

  • Availability
  • Confidentiality
  • Integrity
  • Security
Confidentiality is a key principle of data governance frameworks, ensuring that data is accessible only to authorized users and protected from unauthorized access, disclosure, and modification. This involves implementing access controls, encryption, authentication mechanisms, and data masking techniques to safeguard sensitive information and preserve privacy. By maintaining confidentiality, organizations can mitigate the risk of data breaches, unauthorized disclosures, and regulatory non-compliance, thereby preserving trust and integrity in their data assets.

In a distributed NoSQL database, what is the significance of eventual consistency?

  • Delays data availability until all nodes are consistent
  • Ensures immediate consistency across all nodes
  • Prioritizes availability over immediate consistency
  • Prioritizes consistency over availability
Eventual consistency in a distributed NoSQL database means that while data updates may be propagated asynchronously, the system eventually converges to a consistent state, prioritizing availability over immediate consistency.

________ is a data transformation technique that involves aggregating data over specified time intervals.

  • Data Denormalization
  • Data Interpolation
  • Data Normalization
  • Data Summarization
Data Summarization is the process of aggregating data over specified time intervals, such as hours, days, or months, to provide insights into trends and patterns. It's essential in time-series data analysis.

What are the key features of Google Cloud Bigtable that make it suitable for storing and processing large amounts of data?

  • Data warehousing capabilities
  • Relational data storage
  • Scalability, low latency, and high throughput
  • Strong consistency model
Google Cloud Bigtable is designed for storing and processing large amounts of data with a focus on scalability, low latency, and high throughput. It provides a distributed, NoSQL database service that offers automatic scaling to handle massive workloads seamlessly. Bigtable's architecture, inspired by Google's internal technologies, enables horizontal scaling and efficient data distribution, making it well-suited for applications requiring real-time analytics, time-series data, and high-volume transaction processing. Its eventual consistency model and integration with Google Cloud ecosystem further enhance its capabilities for big data use cases.

What is the purpose of Kafka Connect in Apache Kafka?

  • To integrate Kafka with external systems
  • To manage Kafka topics
  • To monitor Kafka cluster
  • To optimize Kafka performance
Kafka Connect is used to integrate Kafka with external systems, allowing seamless data transfer between Kafka and various data sources.

A ________ is a dimension table that contains hierarchies, such as time, geography, or product.

  • Conformed dimension
  • Degenerate dimension
  • Hierarchical dimension
  • Role-playing dimension
A Role-playing dimension is a dimension table that contains hierarchies, such as time, geography, or product, which can be used in multiple roles within the same data warehouse schema, allowing for flexible and efficient querying and analysis across different perspectives.

Scenario: A social media platform experiences rapid user growth, leading to performance issues with its database system. How would you address these issues while maintaining data consistency and availability?

  • Implementing a caching layer
  • Implementing eventual consistency
  • Optimizing database queries
  • Replicating the database across multiple regions
Replicating the database across multiple regions helps distribute the workload geographically and improves fault tolerance and disaster recovery capabilities. It enhances data availability by allowing users to access data from the nearest replica, reducing latency. Additionally, it helps maintain consistency through mechanisms like synchronous replication and conflict resolution strategies.