1. What is Big Data primarily characterized by?
Answer:
Explanation:
Big Data is primarily characterized by the large volume, high velocity, and varied formats of datasets, which require specific technology and analytical methods for its transformation into value.
2. Which of the following is not one of the three V's of Big Data?
Answer:
Explanation:
The three V's of Big Data are Volume (size of the data), Velocity (speed of data in and out), and Variety (range of data types and sources). Variability is not typically included among the core V's.
3. What is Hadoop?
Answer:
Explanation:
Hadoop is an open-source software framework used for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data and enormous processing power.
4. Which technology is used primarily for real-time Big Data processing?
Answer:
Explanation:
Apache Spark is a unified analytics engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning, and graph processing, which makes it well-suited for real-time Big Data processing.
5. What is a data lake?
Answer:
Explanation:
A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. Unlike a hierarchical data warehouse, data can be stored as-is, without first structuring it.
6. Which of the following is a characteristic of Big Data?
Answer:
Explanation:
Big Data often requires specialized data handling techniques and technologies due to its volume, velocity, and variety, making it different from traditional datasets.
7. In the context of Big Data, what is machine learning?
Answer:
Explanation:
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed, especially valuable in analyzing Big Data.
8. What role does the Internet of Things (IoT) play in Big Data?
Answer:
Explanation:
The Internet of Things (IoT) contributes to Big Data by providing a massive amount of data from connected devices. This data can be analyzed to extract valuable insights.
9. What is data mining in the context of Big Data?
Answer:
Explanation:
Data mining in Big Data is the process of discovering patterns and extracting valuable information from large datasets using statistical methods, machine learning, and database systems.
10. What is Apache Kafka used for in Big Data?
Answer:
Explanation:
Apache Kafka is an open-source stream-processing software platform used for building real-time data pipelines and streaming applications. It is widely used for real-time Big Data processing.
11. In Big Data analysis, what is a 'sentiment analysis'?
Answer:
Explanation:
Sentiment analysis, often applied in Big Data analysis, is the process of computationally identifying and categorizing opinions expressed in a piece of text, especially to determine whether the writer's attitude is positive, negative, or neutral.
12. What does 'NoSQL' stand for in the context of Big Data?
Answer:
Explanation:
NoSQL stands for 'Not Only SQL'. It refers to a type of database design that provides a mechanism for storage and retrieval of data modeled in means other than the tabular relations used in relational databases. NoSQL databases are particularly useful for working with large sets of distributed data.
13. Which of the following is an example of unstructured data in Big Data?
Answer:
Explanation:
Tweets and social media posts are examples of unstructured data, which don't follow a specific format or structure. Big Data encompasses such unstructured data, requiring special processing and analysis techniques.
14. What is the primary challenge in Big Data analytics?
Answer:
Explanation:
The primary challenge in Big Data analytics is to extract meaningful insights from large, diverse, and complex datasets. The sheer volume, velocity, and variety of Big Data make this task challenging.
15. What is 'Predictive Analytics' in the context of Big Data?
Answer:
Explanation:
Predictive analytics involves analyzing historical data to make predictions about future events. In the context of Big Data, it refers to the use of sophisticated data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes.
16. What is the significance of 'Data Governance' in Big Data?
Answer:
Explanation:
Data Governance in Big Data involves managing the availability, usability, integrity, and security of the data. It includes establishing processes to ensure data quality and protection, and managing data assets to benefit the organization.
17. Which Big Data technology is used primarily for distributed storage and parallel processing of large data sets?
Answer:
Explanation:
Apache Hadoop is widely used for distributed storage and parallel processing of large data sets. It's a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models.
18. In Big Data, what is 'Clustering'?
Answer:
Explanation:
In Big Data, 'Clustering' refers to a type of data mining that involves dividing a set of data objects into groups, or clusters, so that the objects in the same cluster are more similar to each other than to those in other clusters.
19. What does ETL stand for in Big Data?
Answer:
Explanation:
ETL stands for Extract, Transform, Load. It is a process in database usage and especially in data warehousing that involves extracting data from outside sources, transforming it to fit operational needs, and loading it into the end target.
20. What is the purpose of data visualization in Big Data?
Answer:
Explanation:
Data visualization in Big Data is used to make the interpretation of large and complex datasets easier. It helps in representing data in a visual context, such as charts, graphs, and maps, making data more accessible and understandable.
21. Which of the following best describes 'Stream Processing' in Big Data?
Answer:
Explanation:
Stream Processing in Big Data refers to processing data in real-time as it arrives. It allows for immediate data processing, often used in scenarios where it is necessary to act quickly on the data as it is received.
22. How does cloud computing support Big Data?
Answer:
Explanation:
Cloud computing supports Big Data by offering scalable, on-demand resources and services over the internet. This includes processing power and storage capacity, which are essential for handling large volumes of data.
23. What is the role of Artificial Intelligence (AI) in Big Data?
Answer:
Explanation:
Artificial Intelligence (AI) plays a significant role in Big Data by automating complex data processing and analysis tasks. AI algorithms can uncover patterns and insights from large datasets, often more efficiently than traditional methods.
24. What are the privacy concerns associated with Big Data?
Answer:
Explanation:
One of the significant privacy concerns associated with Big Data is the potential for unauthorized access and misuse of personal data. The vast amount of data collected and stored can include sensitive personal information, raising privacy and security issues.
25. In Big Data, what is 'Data Wrangling'?
Answer:
Explanation:
Data Wrangling, also known as data munging, in Big Data is the process of cleaning, structuring, and enriching raw data into a desired format for better decision-making in less time.