Database Models and Data Analysis Quiz

Database analysts work with end users and system analysts to model business processes and required data definitions.

Relational databases are the most widely used structure, storing data elements in tables and relating data across tables based on common data elements.

Hierarchical databases arrange fields or records in related groups resembling a family tree with one-to-one relationships.

Network databases are similar to hierarchical databases but more flexible, allowing each child record to have more than one parent record.

SQL allows users to access, describe, define, manipulate data, create and drop databases and tables, create views, and set permissions on tables.

Object-oriented databases are considered key technologies for new generation multimedia web-based applications.

Database management system (DBMS) packages use specific data structures to provide quick, easy access to information stored in databases.

Fundamental database structures include hierarchical, network, relational, object-oriented, and multidimensional models.

Relational databases are more flexible than hierarchical and network models, often built with SQL, and examples include Oracle10g, DB2, SQL Server, Paradox, and Microsoft Access.

SQL (Structured Query Language) is a database computer language designed only for data retrieval in relational databases.

Object-oriented databases are designed to represent complex data relationships effectively and improve database performance, often used in multimedia web-based applications.

They determine data definitions and relationships to be included in the database.

Logical data elements can only include alphabetic characters.

Records are groupings of fields used to describe entity attributes.

A database is a collection of unrelated data elements.

Primary keys hold unique data to identify records in a table.

A Database Management System (DBMS) does not provide benefits such as reduced data redundancy.

DBMS does not offer increased security through authorization control.

The data dictionary stores data definitions and descriptions of the data and database structure.

DBMS utilities do not allow maintenance and automated backup and recovery.

The report generator is not a program for producing readable documents from all or part of a database.

A Database Administrator (DBA) is not responsible for ensuring recoverability, integrity, security, availability, reliability, and performance of the database.

Developing a large database of complex data types does not require careful planning and management.

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Regression analysis only develops mathematical formulas to fit patterns in data, not to predict future trends.

Classification analysis is a statistical pattern-recognition process that can be applied to data sets with non-numerical data.

Regression problems involve predicting discrete values, like house prices in a housing data set.

Classification problems involve predicting categories, like whether a loan should be approved.

All of the big data companies mentioned are IBM, Salesforce, Google, and Oracle.

Big data analytics involves examining large data sets to uncover patterns and correlations.

Big data is not expected to revolutionize measurement and decision-making, leading to new ways of thinking and better insights.

Big data has major uses in medical research, marketing, politics, and entertainment, but not in demand prediction and consumer shopping habits.

Artificial intelligence aims to make computers behave like humans through logic, symbol manipulation, and statistics.

Regression analysis involves finding a line of best fit that minimizes the sum of the squares of the vertical distances of the points from the line.

Classification analysis involves using algorithms such as decision trees, support vector machines, and k-nearest neighbors.

Big data analytics always requires the use of specialized big data tools and platforms.

Object-oriented databases combine data values and operations, and are used in CAD and multimedia web-based applications.

OODBMS supports complex data types more efficiently than relational databases, such as graphic images, video clips, and web pages.

Major relational DBMS vendors add object-oriented modules to their relational software.

Multidimensional database models organize data as facts, dimensions, or numerical answers for interactive analysis in decision-making.

OLAP software is used to provide answers to complex database queries in multidimensional database models.

Multidimensional databases use multidimensional structures to organize data relationships, with data elements viewed as being in cubes.

Hierarchical, network, relational, object-oriented, and multidimensional are different types of database models.

Data mining is the computer-assisted process of analyzing vast amounts of data to extract hidden patterns and discover new knowledge.

Data is fed into a data warehouse through steps like identifying data sources, data fusion, and obtaining data and metadata.

A data warehouse is a special database of cleaned-up data and metadata.

Data mining transforms information into knowledge by analyzing and extracting patterns from data.

Multidimensional databases model data as facts, dimensions, or numerical measures for interactive analysis of large data sets.

True or false: A database is a logically organized collection of unrelated data elements.

True or false: Records are groupings of fields used to describe entity attributes.

True or false: Data is stored hierarchically for easier storage and retrieval.

True or false: SQL (Structured Query Language) is a database computer language designed only for data retrieval in relational databases.

Logical Data Elements are organized into character, field, record, file, and database.

Data is stored hierarchically for easier storage and retrieval.

A file is a collection of related records.

A field is a unit of data containing one or more characters.