Computer Knowledge
Database Management Systems
5,344 Questions
Database Management Systems (DBMS) form the core framework for data storage, retrieval, and security in modern software applications. Concepts such as the E-R model, backup planning, SQL integration, and big data architecture are essential for computer knowledge sections. This hub offers a comprehensive set of practice questions to master DBMS fundamentals and advanced database operations.
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Database Management Systems Questions
Which of the following is NOT a common type of structured data used in Fashion SEO?
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Product schema
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Review schema
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FAQ schema
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Event schema
D
Correct answer
Explanation
Event schema is not a common type of structured data used in Fashion SEO, as it is typically used for events such as concerts, conferences, and meetups, rather than fashion-related content.
What are the three main types of health data?
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Vital statistics, morbidity data, and mortality data.
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Health care utilization data, health status data, and health behavior data.
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Environmental data, occupational data, and social data.
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None of the above.
A
Correct answer
Explanation
The three main types of health data are vital statistics, morbidity data, and mortality data. Vital statistics include data on births, deaths, and marriages. Morbidity data includes data on the incidence and prevalence of diseases and injuries. Mortality data includes data on the causes of death.
Which of the following is not a method of collection organization?
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Classification.
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Cataloging.
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Shelving.
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Indexing.
D
Correct answer
Explanation
Indexing is not a method of collection organization, as it is a method of providing access to resources rather than organizing them.
Which of the following is a common method for constructing ontologies?
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Top-down approach
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Bottom-up approach
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Hybrid approach
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All of the above
D
Correct answer
Explanation
There are different methods for constructing ontologies, including top-down (starting from general concepts and refining them), bottom-up (starting from specific instances and generalizing them), and hybrid (combining both approaches).
In the context of GIS and Big Data, what does the term 'Big Data' primarily refer to?
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A large volume of structured data
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A large volume of unstructured data
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A large volume of spatial data
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A large volume of temporal data
Correct answer
Explanation
Big Data in the context of GIS primarily refers to a large volume of unstructured data, which can include text, images, videos, and sensor data.
What is the process of combining data from different sources into a single dataset called?
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Data Integration
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Data Fusion
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Data Merging
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Data Aggregation
A
Correct answer
Explanation
Data integration involves combining data from different sources into a single dataset, often with the goal of creating a more comprehensive and accurate representation of the real world.
Which type of health data includes information about a patient's lifestyle and behaviors?
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Administrative data
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Clinical data
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Epidemiological data
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Behavioral data
D
Correct answer
Explanation
Behavioral data is a type of health data that includes information about a patient's lifestyle and behaviors, such as their diet, physical activity, and smoking habits.
Which of the following is NOT a type of health data?
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Clinical data
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Demographic data
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Financial data
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Behavioral data
C
Correct answer
Explanation
Financial data is not typically considered health data, as it does not directly relate to the health status of an individual or population.
Which of the following is NOT a common data management standard used in astroinformatics?
C
Correct answer
Explanation
CSV (Comma-Separated Values) is not a common data management standard in astroinformatics, as it is not well-suited for handling large and complex astronomical datasets.
What is the concept of 'Data Lake' in Big Data Analytics?
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A centralized repository for storing raw data
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A platform for processing and analyzing data
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A tool for visualizing data
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A method for data security
A
Correct answer
Explanation
A Data Lake is a centralized repository designed to store large amounts of raw data in its native format. It serves as a central location for storing data from various sources, enabling easy access and analysis by data scientists and analysts.
What is the term used to describe the process of transforming raw data into a structured format?
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Data cleaning
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Data integration
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Data normalization
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Data wrangling
D
Correct answer
Explanation
Data wrangling is the process of transforming raw data into a structured format suitable for analysis. It involves tasks such as data cleaning, data integration, data normalization, and data transformation.
Which technology is used for storing and managing large volumes of unstructured data?
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NoSQL databases
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NewSQL databases
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Graph databases
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All of the above
D
Correct answer
Explanation
NoSQL databases, NewSQL databases, and Graph databases are all technologies used for storing and managing large volumes of unstructured data. NoSQL databases are designed for scalability and flexibility. NewSQL databases combine the scalability of NoSQL with the consistency of traditional relational databases. Graph databases are optimized for storing and querying interconnected data.
Which of the following is NOT a type of health data?
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Vital statistics
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Disease surveillance data
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Health survey data
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Genomic data
D
Correct answer
Explanation
Genomic data is not typically considered health data in the context of disease prevention and public health, as it is more related to genetics and personalized medicine.
What are the three main types of health data?
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Patient demographics, clinical data, and financial data
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Patient demographics, clinical data, and patient satisfaction
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Patient demographics, clinical data, and utilization data
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Patient demographics, clinical data, and outcomes data
C
Correct answer
Explanation
The three main types of health data are patient demographics, clinical data, and utilization data.
Which of the following is NOT a key characteristic of Big Data?
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Volume
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Variety
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Veracity
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Velocity
C
Correct answer
Explanation
Veracity refers to the accuracy and trustworthiness of data, which is not a defining characteristic of Big Data.