Which component of the Hadoop ecosystem provides real-time, random read/write access to data stored in HDFS?
- HBase
- Hive
- Pig
- Spark
HBase is the component of the Hadoop ecosystem that provides real-time, random read/write access to data stored in HDFS (Hadoop Distributed File System). It is a NoSQL database that runs on top of HDFS.
What are the differences between synchronous and asynchronous communication in distributed systems?
- Asynchronous communication is always faster than synchronous communication.
- In synchronous communication, the sender and receiver must be active at the same time, while in asynchronous communication, they operate independently of each other.
- Synchronous communication involves a single sender and multiple receivers, whereas asynchronous communication involves multiple senders and a single receiver.
- Synchronous communication requires a higher bandwidth compared to asynchronous communication.
Synchronous communication requires the sender and receiver to be active simultaneously, with the sender waiting for a response before proceeding, whereas asynchronous communication allows the sender to continue operation without waiting for an immediate response. Asynchronous communication offers benefits such as decoupling of components, better scalability, and fault tolerance, albeit with potential complexities in handling out-of-order messages and ensuring eventual consistency.
Denormalization can lead to faster ________ due to reduced ________ operations.
- Indexing, Joins
- Indexing, Query
- Joins, Indexing
- Queries, Join
Denormalization can lead to faster queries due to reduced join operations. By combining data from multiple normalized tables into a single denormalized table, the need for complex joins is minimized, resulting in faster query execution times, especially for read-heavy workloads.
What is the difference between data cleansing and data validation?
- Data cleansing ensures data integrity, while data validation ensures data availability.
- Data cleansing focuses on ensuring data consistency, whereas data validation focuses on data accuracy.
- Data cleansing involves correcting or removing inaccurate or incomplete data, while data validation ensures that data adheres to predefined rules or standards.
- Data cleansing involves removing duplicates, while data validation involves identifying outliers.
Data cleansing refers to the process of detecting and correcting (or removing) inaccurate or incomplete data from a dataset. It involves tasks such as removing duplicates, correcting typographical errors, filling in missing values, and standardizing formats. On the other hand, data validation ensures that data meets specific criteria or conforms to predefined rules or standards. It involves tasks such as checking data types, ranges, formats, and relationships to ensure accuracy and consistency. Both processes are crucial for maintaining high-quality data in databases and analytics systems.
What is the significance of implementing retry mechanisms in data processing systems?
- Enhancing data privacy
- Ensuring fault tolerance
- Improving data quality
- Minimizing data redundancy
Implementing retry mechanisms in data processing systems is significant for ensuring fault tolerance. Retry mechanisms automatically retry failed tasks, helping systems recover from transient failures without human intervention. This enhances system resilience and reliability, reducing the impact of temporary disruptions on data processing workflows and ensuring consistent data delivery and processing.
Which type of relationship in an ERD indicates that each instance of one entity can be associated with only one instance of another entity?
- Many-to-many relationship
- Many-to-one relationship
- One-to-many relationship
- One-to-one relationship
In an ERD, a one-to-one relationship indicates that each instance of one entity can be associated with only one instance of another entity, and vice versa. It's represented by a straight line between the entities.
What does GDPR stand for in the context of data compliance?
- General Data Protection Regulation
- General Database Processing Rule
- Global Data Privacy Regulation
- Global Digital Privacy Requirement
GDPR stands for General Data Protection Regulation, a comprehensive European Union (EU) legislation designed to protect the privacy and personal data of EU citizens and residents. It imposes strict requirements on organizations handling personal data, including consent mechanisms, data breach notification, data subject rights, and hefty fines for non-compliance, aiming to harmonize data protection laws across the EU and empower individuals with greater control over their personal information.
________ is a data extraction technique that involves extracting data from semi-structured or unstructured sources, such as emails, documents, or social media.
- ELT (Extract, Load, Transform)
- ETL (Extract, Transform, Load)
- ETLT (Extract, Transform, Load, Transform)
- Web Scraping
Web Scraping is a data extraction technique used to extract data from semi-structured or unstructured sources like emails, documents, or social media platforms, enabling analysis and processing of the data.
The process of defining policies, procedures, and standards for data management is part of ________ in a data governance framework.
- Data Compliance
- Data Governance
- Data Quality
- Data Stewardship
In a data governance framework, the process of defining policies, procedures, and standards for data management falls under the domain of Data Governance. Data governance encompasses the establishment of overarching principles and guidelines for managing data effectively across the organization. It involves defining rules and best practices to ensure data is managed, accessed, and used appropriately to support organizational objectives while maintaining compliance and mitigating risks.
The choice between data modeling tools such as ERWin and Visio depends on factors like ________.
- Availability of training resources and online tutorials
- Color scheme and user interface
- Cost, complexity, and specific requirements
- Operating system compatibility and file format support
The choice between data modeling tools such as ERWin and Visio depends on factors like cost, complexity, specific requirements of the project, and the availability of features required for the task.