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.
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.
________ 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.
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 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.
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.
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.
In normalization, the process of breaking down a large table into smaller tables to reduce data redundancy and improve data integrity is called ________.
- Aggregation
- Decomposition
- Denormalization
- Normalization
Decomposition is the process in normalization where a large table is broken down into smaller tables to reduce redundancy and improve data integrity by eliminating anomalies.
Scenario: Your organization stores customer data, including personally identifiable information (PII). A data breach has occurred, and customer data has been compromised. What steps should you take to mitigate the impact of the breach and ensure compliance with relevant regulations?
- Deny the breach, silence affected customers, modify security policies, and avoid regulatory reporting
- Downplay the breach, blame external factors, delete compromised data, and continue operations as usual
- Ignore the breach, improve security measures, terminate affected employees, and conduct internal training
- Notify affected customers, conduct a thorough investigation, enhance security measures, and report the breach to relevant authorities
In the event of a data breach, it's crucial to take immediate action to mitigate its impact and comply with regulations. This includes notifying affected customers promptly to mitigate potential harm, conducting a thorough investigation to understand the breach's scope and root cause, enhancing security measures to prevent future incidents, and reporting the breach to relevant authorities as required by law. Transparency, accountability, and proactive remediation are essential to rebuilding trust and minimizing regulatory penalties.
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.
Apache ________ is a distributed messaging system commonly used for building real-time data pipelines and streaming applications.
- Flume
- Kafka
- RabbitMQ
- Storm
Apache Kafka is a distributed messaging system known for its high throughput, fault-tolerance, and scalability. It is commonly used in real-time data processing scenarios for building data pipelines and streaming applications, where it facilitates the ingestion, processing, and delivery of large volumes of data with low latency and high reliability.
________ is a data transformation method that involves splitting a single data field into multiple fields based on a delimiter.
- Data Aggregation
- Data Merging
- Data Pivoting
- Data Splitting
Data Splitting is a transformation technique used to split a single data field into multiple fields based on a specified delimiter, such as a comma or space. It's commonly used in data preprocessing tasks.