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Introduction to Computer Science

Review Questions

Introduction to Computer ScienceReview Questions

Review Questions

1 .
What statement best describes the differences among data, information, and knowledge?
  1. Data are collected from random sources. Information is gathered from specific sources. Knowledge is the process of reading and understanding data and information.
  2. Data are information that was targeted to be collected and stored by a system or application. Information is the bulk data that have not been analyzed to determine to keep or delete. Knowledge is the underlying decision on what information to turn into data.
  3. Knowledge is the process of reading and understating information and data. Information is data that have been collected from targeted research of online and academic sources. Data are information that was collected from research and development experiments.
  4. Data are the raw data without meaning. Information is processing and formatting the data. Knowledge is the process of using and analyzing the information.
2 .
What does a data steward do?
  1. They ensure that the enterprise's actual business data and the metadata are accurate, accessible, secure, and safe.
  2. They have the authority to ultimately decide on the access to, and usage of, the data.
  3. They are responsible for creating, implementing, and maintaining the database management system.
  4. They design conceptual data model (blueprints) to bridge the gap between the business processes and the IT environment.
3 .
What are three examples of data quality parameters?
  1. size, accuracy, and variety of sources
  2. accuracy, age of data, and size
  3. accuracy, security, and variety of sources
  4. accessibility, accuracy, and security
4 .
Define data governance.
5 .
What is metadata and what is involved in cataloging them?
6 .
Data science is a combination of what domains?
  1. computer science, and mathematics and statistics
  2. computer science and business area applications
  3. computer science, mathematics and statistics, and business area applications
  4. mathematics and statistics, and business area applications
7 .
What type of data model focuses on scalability and easily copes with irregular or highly volatile data structures?
  1. relational DBMS
  2. XML DBMS
  3. hierarchical DBMS
  4. NoSQL DBMS
8 .
A federated DBMS architecture can be described as
  1. a uniform interface to multiple underlying data sources, which hide the underlying storage details to facilitate data access.
  2. where the data are maintained on a centralized server at a single location.
  3. where the DBMS and database are hosted by a third-party cloud provider.
  4. an architecture that stores all data in internal memory instead of slower external storage.
9 .
What are the three layers into which an n-tier DBMS architecture divides an application?
  1. client side, server side, virtual
  2. physical, logic, virtual
  3. presentation, logic, data
  4. front-end, back-end, network
10 .
What is physical data independence?
  1. the use of multiple physical storage devices such as local servers and external hard drives where data on one device is not dependent on data on other physical storage devices
  2. a separation of the conceptual level from the physical level
  3. where the data stored on local devices is not dependent on data stored in the cloud.
  4. a separation of logical layers and presentation layers of data
11 .
Give a few examples of data models and explain how they differ from one another.
12 .
Give examples of DBMS users.
13 .
What type of systems is described where the presentation layer is only on the client device but the application and data layers are on the server devices?
  1. thin-client
  2. fat-client
  3. distributed application
  4. parallel processing
14 .
What is the primary key?
  1. the special string of characters to unlock a table for editing
  2. a special unique identifier for each table record
  3. the first object in the table that locks in the format for that table
  4. the first field of an object
15 .
What are some of the relational algebra operations?
16 .
Explain how QBE works.
17 .
What is a key constraint in the relational model?
18 .
What is an NFNF DBMS?
  1. a database data model that does meet any of the conditions of database normalization defined by the relational model
  2. a database data model that does not meet any of the conditions of database normalization defined by the relational model
  3. a database data model that does meet all of the conditions of database normalization defined by the relational model
  4. a database data model that takes a nonrelational data model and formats the tables to conform to a standard format
19 .
Which term is described as a simple database that uses an associative array that stores only key-value pairs, provides basic functionality for retrieving the value associated with a known key, and works best with a simple database schema?
  1. tuple and document stores
  2. graph-based databases
  3. key-value stores
  4. column-oriented databases
20 .
What is a data lake?
  1. a scaled-down version of a data warehouse aimed at meeting the information needs of a homogeneous small group of end users
  2. data stored without organization to make retrieval easy
  3. a large data repository that stores raw data and can be set up without having to first define the data structure and schema
  4. centralizes an enterprise’s data from its databases, supporting the flow of data from operational systems to analytics/decision systems by creating a single repository of data from various sources both internal and external
21 .
How many schemas can a data warehouse consist of?
  1. Many; there is no defined number of schemas.
  2. One; all tables must conform to one schema.
  3. None; schemas are undefined in data warehouses.
  4. There is one for each table in the data warehouse.
22 .
Which is one of the five Vs of big data?
  1. verified data
  2. validated data
  3. volatile data
  4. volume of data
23 .
What is the definition of data governance?
  1. It is a technique that hides the physical location of data and uses data integration patterns to produce a unified data view.
  2. It uses enterprise application integration (EAI) corresponding to the synchronous or asynchronous propagation of updates in a source system to a target system.
  3. It aims to set up a company-wide controlled and supported approach toward data quality that is accompanied by data quality management processes.
  4. It uses enterprise information integration (EII) to provide a unified view over data sources.
24 .
Is MapReduce part of Hadoop?
25 .
What is informatics and how does it relate to information systems?
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