Which normal form addresses the issue of transitive dependency?
- Boyce-Codd Normal Form (BCNF)
- First Normal Form (1NF)
- Second Normal Form (2NF)
- Third Normal Form (3NF)
Third Normal Form (3NF) addresses the issue of transitive dependency by ensuring that all attributes in a table are dependent only on the primary key, eliminating indirect relationships between attributes.
Kafka uses the ________ protocol for communication between clients and servers.
- Apache Avro
- HTTP
- Kafka
- TCP
Kafka uses the Kafka protocol for communication between clients and servers. This protocol is specifically designed for efficient and reliable messaging in the Kafka ecosystem.
The documentation of data modeling processes should include ________ to provide clarity and context to stakeholders.
- Data Dictionary
- Flowcharts
- SQL Queries
- UML Diagrams
The documentation of data modeling processes should include a Data Dictionary to provide clarity and context to stakeholders by defining the terms, concepts, and relationships within the data model.
Apache Airflow provides a ________ feature, which allows users to monitor the status and progress of workflows.
- Logging
- Monitoring
- Scheduling
- Visualization
Apache Airflow offers a robust monitoring feature that allows users to track the status and progress of workflows in real-time. This feature provides insights into task execution, dependencies, and overall workflow health, enabling users to identify and troubleshoot issues effectively. Monitoring is essential for ensuring the reliability and efficiency of data pipelines orchestrated by Apache Airflow.
The process of optimizing the performance of SQL queries by creating indexes, rearranging tables, and tuning database parameters is known as ________.
- Database Optimization
- Performance Enhancement
- Query Tuning
- SQL Enhancement
Query tuning involves various activities such as creating indexes, optimizing SQL queries, rearranging tables, and adjusting database parameters to improve performance.
Which of the following statements about Apache Hadoop's architecture is true?
- Hadoop follows a master-slave architecture
- Hadoop is primarily designed for handling structured data
- Hadoop operates only in a single-node environment
- Hadoop relies exclusively on SQL for data processing
Apache Hadoop follows a master-slave architecture where the NameNode acts as the master and manages the Hadoop Distributed File System (HDFS), while DataNodes serve as slaves, storing and processing data.
How do data modeling tools like ERWin or Visio facilitate collaboration among team members during the database design phase?
- By allowing integration with project management tools for task tracking
- By enabling concurrent access and version control of the data model
- By offering real-time data validation and error checking
- By providing automated code generation for database implementation
Data modeling tools like ERWin or Visio facilitate collaboration by allowing team members to concurrently access and modify the data model while maintaining version control, ensuring consistency across edits.
The concept of ________ allows real-time data processing systems to respond to events or changes immediately.
- Batch processing
- Event-driven architecture
- Microservices architecture
- Stream processing
Event-driven architecture is a design approach that enables real-time data processing systems to respond to events or changes immediately, without waiting for batch processing cycles. This architecture allows systems to react dynamically to incoming events or triggers, enabling timely actions, notifications, or updates based on real-time data streams. It is well-suited for applications requiring low latency, high scalability, and responsiveness to dynamic environments.
What role does data profiling play in data modeling best practices?
- Defining data schema
- Generating sample data
- Identifying data quality issues
- Optimizing database performance
Data profiling in data modeling involves analyzing and understanding the quality and characteristics of data, including identifying anomalies and inconsistencies, which is crucial for ensuring data quality.
Which of the following is a characteristic of Data Lakes?
- Schema enforcement
- Schema normalization
- Schema-on-read
- Schema-on-write
A characteristic of Data Lakes is schema-on-read, meaning that the structure of the data is applied when it's read rather than when it's written, allowing for greater flexibility and agility in data analysis.
Scenario: You are tasked with optimizing the performance of a Spark application that involves a large dataset. Which Apache Spark feature would you leverage to minimize data shuffling and improve performance?
- Broadcast Variables
- Caching
- Partitioning
- Serialization
Partitioning in Apache Spark allows data to be distributed across multiple nodes in the cluster, minimizing data shuffling during operations like joins and aggregations, thus enhancing performance by reducing network traffic and improving parallelism.
Scenario: In a healthcare organization, data quality is critical for patient care. What specific data quality metrics would you prioritize to ensure accurate patient records?
- Completeness, Accuracy, Consistency, Timeliness
- Integrity, Transparency, Efficiency, Usability
- Precision, Repeatability, Flexibility, Scalability
- Validity, Reliability, Relevance, Accessibility
In a healthcare organization, ensuring accurate patient records is paramount for providing quality care. Prioritizing metrics such as Completeness (ensuring all necessary data fields are filled), Accuracy (data reflecting the true state of patient information), Consistency (uniform format and standards across records), and Timeliness (up-to-date and relevant data) are crucial for maintaining data quality and integrity in patient records. These metrics help prevent errors, ensure patient safety, and facilitate effective medical decision-making.