Sfsu: Isys 363 - Chapter 5

Data redundancy refers to the duplication of data in multiple data files. This can occur when the same information is stored in different places, leading to unnecessary storage and potential inconsistencies. It is considered a disadvantage as it increases storage requirements and can lead to data integrity issues. Data multiplication, on the other hand, is not a widely recognized term in the context of data management. Data independence refers to the ability to make changes to the data structure without affecting the applications using the data. While data redundancy is a common issue in relational models, it is not exclusive to them.

SQL (Structured Query Language) is the most prominent data manipulation language today. It is widely used in relational database management systems (RDBMS) to manage and manipulate data. SQL allows users to query, insert, update, and delete data in a database. It is a standardized language that is supported by various database systems such as Oracle, MySQL, and Microsoft SQL Server. Access, DB2, and Crystal Reports are not data manipulation languages like SQL; they are database management systems or reporting tools.

The first step in managing data for a firm is to identify the data needed to run the business. This involves determining what type of data is necessary for the firm's operations and decision-making processes. By identifying the required data, the firm can then focus on collecting, organizing, and storing the relevant information. This step is crucial as it sets the foundation for effective data management and ensures that the firm is working with the right data to achieve its goals.

A data mart typically focuses on a single subject area or line of business, which allows for a more streamlined and focused construction process. By narrowing down the scope of the data mart to a specific area, it requires less effort and resources compared to building a comprehensive data warehouse that encompasses all aspects of the organization. This targeted approach also enables quicker implementation and lower costs as it eliminates the need to gather and integrate data from various sources across the entire organization.

Data redundancy refers to the duplication of data in a database. When data is duplicated across different sources, it becomes difficult for companies to integrate and manage this data effectively. This duplication can lead to inconsistencies, errors, and inefficiencies in systems such as customer relationship management, supply chain management, or enterprise systems. Therefore, the confusion created by data redundancy makes it challenging for companies to create integrated systems that can seamlessly integrate data from different sources.

An attribute is a characteristic or quality that describes an entity. It provides additional information about the entity and helps to distinguish it from other entities. In the context of databases or data modeling, an attribute represents a specific piece of information that can be stored and manipulated. Therefore, out of the given options, "attribute" is the correct term to describe a characteristic or quality of an entity.

The join operation in a relational database combines two or more tables based on a common column or key, allowing the user to retrieve information from multiple tables in a single query. By matching the values in the specified column, the join operation combines the rows from different tables, providing the user with a result set that includes information from both tables. This allows the user to access more comprehensive and meaningful data that may not be available in a single table.

The relational database management system (DBMS) treats data as if they were stored in two-dimensional tables. In a relational DBMS, data is organized into tables with rows and columns, where each row represents a record and each column represents a specific attribute or field of the data. This model allows for efficient storage, retrieval, and manipulation of data through structured query language (SQL) operations. OODBMS, pre-digital DBMS, and hierarchical DBMS do not follow the same table-based structure as relational DBMS.

OLAP (Online Analytical Processing) is the tool that enables users to view the same data in different ways using multiple dimensions. It allows users to analyze data from various perspectives and dimensions, such as time, geography, and product. OLAP provides a multidimensional view of data, allowing users to drill down, slice, and dice data to gain insights and make informed decisions. It is commonly used in business intelligence and data analysis to support reporting, planning, and decision-making processes.

The relationship between entities and attributes is that an entity represents a real-world object or concept, while an attribute represents a characteristic or property of that entity. In this case, the entity CUSTOMER represents a customer, and the attribute ADDRESS represents the address of that customer. This relationship is logical and makes sense, as a customer can have an address associated with them.

A data warehouse is a central repository that stores and organizes data from various sources for analysis and reporting purposes. It contains both historical and current internal data, which refers to data generated and collected within the organization. Historical data provides insights into past trends and patterns, while current data allows for real-time analysis and decision-making. Additionally, a data warehouse may also include internal and external data sources, which further enrich the analysis by incorporating data from both within and outside the organization.

An entity-relationship diagram is a schematic representation of the relationships between entities in a database. It visually shows how different entities are related to each other through various relationships such as one-to-one, one-to-many, or many-to-many. It helps in understanding the structure and organization of the database, making it easier to design, implement, and manage the database system.

In a relational database, the select operation is used to retrieve specific rows from a table based on certain conditions. The project operation is used to retrieve specific columns from a table. The join operation is used to combine rows from two or more tables based on a related column. These three operations, select, project, and join, are fundamental in developing useful sets of data in a relational database.

OLAP, or Online Analytical Processing, is a tool that allows users to obtain online answers to ad hoc questions in a rapid amount of time. This means that users can easily and quickly access and analyze data to find answers to specific questions or make informed decisions. OLAP provides a multidimensional view of data, allowing users to slice and dice information in various ways to gain insights. It is designed to handle large volumes of data and provide fast query response times, making it an efficient tool for users to obtain online answers in a timely manner.

A library's card catalog is an example of a pre-digital database because it was a physical system used to organize and access information about books in a library. The card catalog consisted of index cards, each representing a book, and allowed users to search for books based on author, title, or subject. This system was used before the advent of digital databases and online catalogs, making it a suitable example of a pre-digital database.

An object-oriented DBMS is capable of handling multimedia data because it allows for the storage and retrieval of complex objects, such as images, videos, and audio files, along with their associated metadata. This type of database management approach supports the storage of multimedia data in a structured manner, allowing for efficient querying and manipulation of the data. Unlike other approaches like hierarchical, relational, or network DBMS, an object-oriented DBMS provides more flexibility and scalability for handling multimedia data.

In a table for customers, the information about a single customer would reside in a row. Each row in a table represents a unique record or entry, and in this case, each row would contain the information related to a specific customer. The columns in the table would represent different attributes or fields of the customer data, such as name, address, phone number, etc. Therefore, the correct answer is row.

Businesses use text mining tools to search and analyze unstructured data sets, such as e-mails and memos. Text mining involves the process of extracting meaningful information and patterns from large amounts of unstructured text data. This allows businesses to gain insights, identify trends, and make informed decisions based on the analysis of textual data. OODBMS, OLAP, and Web mining are not specifically designed for analyzing unstructured text data, making text mining the correct answer in this context.

Business intelligence refers to the tools and technologies used for gathering, storing, analyzing, and providing access to large amounts of data in order to support better business decision-making. These tools help users consolidate and analyze data from various sources, such as databases, spreadsheets, and external sources, to gain insights and make informed decisions. Business intelligence tools often include features such as data visualization, reporting, and predictive analytics to help businesses understand trends, identify opportunities, and improve their overall performance.

Normalization is the process of organizing data in a database to eliminate redundancy and improve efficiency. It involves breaking down a database into smaller, more manageable tables and establishing relationships between them. This helps in eliminating data duplication and ensures that each piece of information is stored in only one place. Normalization also helps in avoiding many-to-many relationships, where multiple instances of one entity are associated with multiple instances of another entity, which can lead to data inconsistency and complexity. Therefore, normalization is the correct answer in this context.

The logical view of a database presents data as they would be perceived by end users. This means that it provides a representation of the data that is meaningful and easily understandable to the users. It may involve organizing and structuring the data in a way that is intuitive and user-friendly, such as using tables, forms, and queries. This view hides the complexities of the underlying storage media and focuses on presenting the data in a way that is relevant and useful to the end users.

A data dictionary is a file that stores information about data elements and their characteristics, such as how they are used, physically represented, owned, authorized, and secured. It serves as a central repository for metadata, providing a comprehensive understanding of the data within a system or organization. This information is essential for data management, data governance, and ensuring data quality and consistency.

DBMS's typically include report-generating tools to display data in an easier-to-read format. These tools allow users to organize and present data in a structured manner, making it more comprehensible and accessible. By generating reports, DBMS's enable users to summarize and visualize large amounts of data, facilitating decision-making and analysis. This feature enhances data presentation by providing clear and concise information, improving the overall usability and effectiveness of the database system.

The inclusion of DNA from people who commit misdemeanors is seen as controversial because it exposes them to risks they would not otherwise face, such as mistakes in DNA collection and wrongful conviction. This means that innocent individuals may be wrongly implicated in crimes due to errors in DNA processing, potentially leading to unjust punishments. This raises concerns about the fairness and accuracy of using DNA as evidence in criminal investigations, and the potential violation of individuals' rights and privacy.

Data mining is a process that involves discovering patterns, relationships, and insights within large datasets. It uses various techniques such as statistical analysis, machine learning, and artificial intelligence to uncover hidden relationships and patterns that are not easily visible. By finding hidden relationships in data, users can gain valuable insights and make informed decisions. This makes the given answer, "find hidden relationships in data," the correct choice as it accurately describes one of the main purposes of data mining.

The most basic business database is comprised of five tables: a table for customers, a table for employees, a table for suppliers, a table for parts, and a table for sales. This answer includes all the essential components necessary for a basic business database, covering the main entities involved in a business operation such as customers, employees, suppliers, parts, and sales. Each table represents a different aspect of the business and allows for efficient storage and retrieval of relevant information.

Data scrubbing refers to the process of detecting and correcting data in a database or file that are incorrect, incomplete, improperly formatted, or redundant. It involves identifying and removing any inconsistencies or errors in the data to ensure its accuracy and reliability. This process helps in maintaining data integrity and improving the overall quality of the database or file.

In a relational database, a record is referred to as a tuple. A tuple represents a single row in a table and contains a collection of attributes or fields that define the data for that record. The term "tuple" is commonly used in the context of relational algebra and database theory to describe a finite sequence of values that corresponds to a specific record in a table. Therefore, "tuple" is the correct term to describe a record in a relational database.

A field identified in a table as holding the unique identifier of the table's records is called a primary key. This field is used to uniquely identify each record in the table and ensures that there are no duplicate records. It is an essential component of a relational database as it allows for efficient data retrieval and manipulation. Other terms like key field, primary field, and unique ID may be used interchangeably, but the most commonly used term for this concept is the primary key.

A one-to-one relationship between two entities is symbolized in a diagram by a line that ends in two short marks. This symbol indicates that each entity in one set is associated with exactly one entity in the other set, and vice versa. The two short marks represent the uniqueness and exclusivity of the relationship between the entities.

Data warehouse systems provide easy-to-use tools for managers to easily update data. This statement is not true because data warehouses are designed to store and analyze data, not to update it. The purpose of a data warehouse is to provide a centralized and consistent source of data for analysis and decision making, rather than serving as a platform for data entry and updates.

The relational database is named for the relationships between entities. In a relational database, entities are represented as tables, and the relationships between these entities are established through the use of keys and foreign keys. These relationships allow for the organization and retrieval of data in a structured and efficient manner. By understanding the relationships between entities, users can query the database and retrieve information that is relevant to their needs.

A DBMS (Database Management System) is a software that manages databases. It typically includes features such as data manipulation language (to manipulate data), report generation tools (to generate reports), and a data dictionary (to store metadata about the database). However, a query wizard tool is not a typical feature of a DBMS. Query wizards are typically found in database applications or query tools that provide a user-friendly interface for creating and executing queries, but they are not an inherent part of a DBMS itself.

The given answer is "Desktop relational DBMS." This implies that Access is a database management system (DBMS) specifically designed for desktop computers. Unlike other options such as DBMS for small handheld computing devices, mainframe relational DBMS, or DBMS for midrange computers, Access is suitable for managing databases on a desktop computer.

The correct answer is data manipulation language. This is the specialized language that programmers use to add and change data in the database. It allows them to perform operations such as inserting, updating, and deleting data. The other options listed are not specifically focused on manipulating data in the database.

MySQL is a popular open-source DBMS (Database Management System) that is widely used for managing and organizing data. It is not specifically designed for small handheld computing devices or mainframe systems, but rather for desktop systems. As an open-source DBMS, it is freely available and has a large community of developers contributing to its continuous development and improvement.

A one-to-many relationship between two entities is symbolized in a diagram by a line that ends with a crow's foot topped by a short mark. This notation represents that one entity is associated with multiple instances of another entity. The crow's foot indicates the "many" side of the relationship, while the short mark represents the "one" side. This notation helps to visually represent the relationship between entities and is commonly used in entity-relationship diagrams.

DB2 is a mainframe relational DBMS. This means that it is a database management system specifically designed for large-scale mainframe computers, which are powerful and capable of handling extensive data processing. Additionally, DB2 is a relational DBMS, meaning it organizes data into tables with relationships between them, allowing for efficient data storage and retrieval. It is not designed for small handheld computing devices, desktop computers, or as an internet DBMS.

The correct answer is "DBMS for midrange computers." This is because Microsoft SQL Server is a relational database management system (DBMS) that is designed to run on midrange computers, which are typically more powerful and capable of handling larger amounts of data compared to small handheld devices or desktop computers. Additionally, SQL Server is commonly used in enterprise-level environments and supports advanced features such as high availability, scalability, and security, making it suitable for midrange computer systems.

The select operation creates a subset consisting of all records in the file that meet the stated criteria. This means that only the records that satisfy the specified conditions will be included in the subset. The select operation is used to filter and retrieve specific data from a table based on certain conditions or criteria. It allows the user to extract the desired information from a larger set of data by specifying the criteria that the records must meet.

The question asks for an exception among the given options for DBMS for midrange computers. DB2, Oracle, and Microsoft SQL Server are all popular and widely used DBMS for midrange computers. However, Microsoft Access is not typically considered a DBMS for midrange computers, as it is more commonly used as a desktop database management system for small-scale applications.

Associations in data mining refer to occurrences that are linked to a single event. This means that certain events or incidents are connected to a specific occurrence. Data mining techniques can be used to identify these associations and understand the relationship between different occurrences and events. It helps in uncovering patterns and connections within the data, allowing for better analysis and decision-making.

A DBMS (Database Management System) allows for the physical database to be accessed and manipulated through different logical views. This means that users can interact with the database using different perspectives or representations, without directly dealing with the underlying physical structure or organization of the data. The DBMS handles the translation between the logical views and the physical storage, providing a layer of abstraction that simplifies data management and access for users.

An object-relational DBMS is useful for storing Java applets because it combines the features of both object-oriented and relational databases. It allows for the storage and retrieval of complex data types, such as Java objects, while also providing the ability to handle large numbers of transactions efficiently. This makes it a suitable choice for applications that require both the flexibility of object-oriented programming and the scalability of a relational database system.

An alternative to using application server software for interfacing between a Web server and back-end databases is CGI. CGI stands for Common Gateway Interface and it is a standard protocol that allows web servers to communicate with external programs or scripts. It enables the web server to pass data between the user's request and the back-end database, making it a suitable alternative to application server software for this purpose. HTML, Java, and SQL are not alternatives to application server software for interfacing with back-end databases.

Oracle Database Lite is a DBMS specifically designed for small handheld computing devices. This means that it is a database management system that is optimized to run on devices such as smartphones, tablets, and other portable devices with limited computing power and storage capacity. Oracle Database Lite allows users to store and manage data on these devices, providing them with the ability to access and manipulate data even when they are offline or have limited connectivity. It is a lightweight and efficient solution for mobile data management.

A table that links two tables that have a many-to-many relationship is called an intersection relation. This table serves as a bridge between the two tables, allowing for the association of multiple records from each table. It typically contains the primary keys of both tables as foreign keys, creating a junction point where the relationships between the records can be established. The intersection relation helps in resolving the complexity of many-to-many relationships by providing a centralized location to manage and query the associations between the two tables.

Sequences in data mining refer to events that are linked over time. This means that the data mining process identifies patterns or relationships between events that occur in a specific order or sequence. By analyzing these sequences, valuable insights can be gained, such as predicting future events or understanding the cause and effect relationships between different events.

Web usage mining is the correct answer because it involves analyzing user interaction data recorded by Web servers to discover patterns and trends. This technique helps in understanding user behavior, preferences, and interests, which can be used to improve website design, personalize content, and optimize marketing strategies. Web server mining focuses on analyzing the server logs and performance data, while web structure mining examines the link structure of websites, and web content mining deals with extracting useful information from web pages.

The project operation creates a subset consisting of columns in a table. This means that it selects specific columns from a table and discards the rest, resulting in a new table with only the selected columns. This operation is useful when the user only needs certain information from a table and wants to simplify the data by focusing on specific attributes.