MIS Chapter 3 Study Test

Recovery is the process of reinstalling the backup information in the event the information was lost. This involves restoring the data from a backup source to its original location or a new location. It is an essential step in data management to ensure that lost or corrupted data can be recovered and business operations can resume smoothly.

A DBMS (Database Management System) is a software that helps in organizing and structuring a database, allowing users to efficiently access and utilize the information stored within it. It provides a set of tools and functionalities for creating, managing, and manipulating databases, ensuring data integrity, security, and efficient retrieval. With a DBMS, users can define the structure of the database, create tables, define relationships between tables, and perform various operations like querying, inserting, updating, and deleting data. Therefore, a DBMS is essential for specifying the logical organization of a database and facilitating easy access and utilization of information.

A primary key is a field or group of fields that uniquely identifies each record in a database table. It is used to ensure the uniqueness and integrity of the data within the table. The primary key is crucial for maintaining data consistency and for establishing relationships between tables in a relational database. It allows for efficient searching, sorting, and indexing of records.

Business intelligence refers to collective information that gives you the ability to make effective, important, and often strategic business decisions. It involves gathering and analyzing data from various sources to provide insights and support decision-making processes. Business intelligence tools and techniques help organizations to understand their market, competitors, customers, and internal operations better, thereby enabling them to make informed decisions that can drive growth and success.

The relational database model is the most popular model for creating databases because it organizes data into tables with rows and columns, allowing for efficient storage and retrieval of information. This model uses relationships between tables, defined by keys, to establish connections and maintain data integrity. It provides a flexible and scalable structure, making it suitable for various applications and industries. Additionally, the relational model supports complex queries and allows for easy data manipulation and analysis, making it a preferred choice for database management systems.

A backup is a duplicate copy of the information stored on a computer. It is created to ensure that data can be recovered in case of loss, damage, or accidental deletion. Backups are essential for protecting important files and preventing data loss.

Analytics is the science of fact-based decision making. It involves the use of data, statistical analysis, and mathematical models to extract insights and make informed decisions. By analyzing data, patterns and trends can be identified, allowing businesses and organizations to make strategic decisions and solve complex problems. Analytics helps in understanding customer behavior, optimizing processes, improving efficiency, and identifying opportunities for growth. It plays a crucial role in various industries, such as marketing, finance, healthcare, and sports, by providing valuable insights that drive decision-making processes.

Query optimization facilities are designed to find the most efficient way to retrieve information from a database. They analyze the structure of the query and the available indexes and statistics to determine the optimal execution plan. By doing so, they can minimize the time and resources required to retrieve the desired information, thus providing the "shortest route" to the information. This helps to improve the overall performance and efficiency of the database system.

Security management facilities allow you to control who has access to what information and what type of access those people have. These facilities provide the necessary tools and mechanisms to enforce security policies, manage user accounts, authenticate users, and grant or revoke privileges. By using security management facilities, organizations can ensure that only authorized individuals can access sensitive information and that they have the appropriate level of access based on their roles and responsibilities.

Before adding any information to a relational database, it is necessary to define the logical structure of the database. This includes determining the tables, relationships between tables, and the attributes or columns within each table. By defining the logical structure, it provides a framework for organizing and storing the data efficiently and accurately. It also helps ensure data integrity and allows for effective querying and retrieval of information from the database.

A digital dashboard is a tool that presents information from multiple sources in a customized format for knowledge workers. It allows them to access and analyze key data in a user-friendly way, making it easier to make informed decisions and track progress towards goals. By displaying relevant information on a computer screen, a digital dashboard helps individuals stay organized and efficient in their work.

In a database, a primary key is a field or combination of fields that uniquely identifies each record. In this scenario, if the phone number is used as a unique identifier for customers in a clothing store, it would be considered a primary key. This means that each customer would have a different phone number associated with them, allowing for easy and accurate identification of individual customers.

Integrity constraints are used to ensure the quality and accuracy of information in a relational database. These constraints define rules and restrictions on the data that is stored in the database, ensuring that it remains consistent and reliable. They enforce rules such as data type validation, uniqueness of values, referential integrity, and domain constraints. By enforcing these constraints, the integrity of the data is maintained, preventing inconsistencies and errors in the database.

A foreign key is a primary key of one file that appears in another file. This means that the foreign key in the second file references the primary key in the first file, creating a relationship between the two files. This relationship allows for data integrity and the ability to connect related information between the two files.

A relational database model organizes and accesses information based on its logical structure rather than its physical structure. In a relational database, data is stored in tables with rows and columns, and relationships between tables are established using keys. This allows for efficient querying and manipulation of data, as well as flexibility in adding or modifying the structure of the database without affecting the data itself.

An attribute refers to a specific piece of information that is stored in a database file. It represents a characteristic or property of an entity in the database. Attributes define the different types of data that can be stored in a database table, such as names, dates, numbers, or descriptions. By organizing data into attributes, databases can efficiently store and retrieve information based on specific criteria.

Databases and DBMSs are the technology tools that directly support OLTP (Online Transaction Processing). OLTP involves managing and processing real-time transactions, such as sales, orders, and payments, in a database system. Databases store and organize the data, while DBMSs (Database Management Systems) provide the software and tools to manage and manipulate the data efficiently. Therefore, databases and DBMSs play a crucial role in supporting OLTP operations.

A database is a collection of information that is organized and accessed based on the logical structure of that information. It allows for efficient storage, retrieval, and manipulation of data, making it easier to manage and analyze large amounts of information. Databases are commonly used in various applications and industries to store and retrieve data in a structured and organized manner.

The senior manager in this scenario is analyzing internal and external information to analyze marketing campaigns and their effect on customer buying habits. This requires a tool that can handle large amounts of data and provide analytical capabilities. Online analytical processing (OLAP) is a type of application that allows users to analyze multidimensional data from different perspectives. It is specifically designed for complex analysis and reporting tasks, making it the most suitable option for the senior manager in this situation.

Data-mining is the correct answer because it is a software tool used to query information stored in a data warehouse. Data-mining involves extracting patterns and valuable insights from large sets of data, allowing users to analyze and discover relationships, trends, and patterns within the data. This tool is specifically designed for decision support and helps organizations make informed business decisions based on the data stored in their data warehouse.

A data warehouse is a special form of a database that contains information gathered from operational databases for the purpose of supporting decision-making tasks. It is designed to store large amounts of historical and current data in a structured and optimized manner, allowing for efficient retrieval and analysis. The data warehouse consolidates data from various sources, cleanses and transforms it, and organizes it in a way that is conducive to reporting, analysis, and data mining. By providing a centralized and integrated view of data, a data warehouse enables businesses to make informed decisions based on accurate and consistent information.

Database administration is responsible for the more technical and operational aspects of managing information repositories. This function involves tasks such as designing, implementing, and maintaining databases, ensuring data security and integrity, and optimizing database performance. Database administrators also handle tasks like data backup and recovery, user access management, and troubleshooting database issues. They play a crucial role in ensuring that information repositories are well-managed and meet the organization's needs.

Query-and-reporting tools are the data-mining tools that would be used to quickly build reports without having to write programming code in a data warehouse. These tools allow users to retrieve and analyze data from the warehouse using a user-friendly interface, eliminating the need for programming skills. They provide a simplified way to create and customize reports based on specific requirements, making them a convenient choice for non-technical users who need to generate reports efficiently.

KPIs, or Key Performance Indicators, are the most essential and important quantifiable measures used in analytics initiatives to monitor the success of a business activity. KPIs help organizations track progress towards their goals and objectives, providing a clear understanding of performance and identifying areas for improvement. They are specific, measurable, and relevant metrics that enable businesses to evaluate their performance and make data-driven decisions. DPIs, QBEs, and SQLs are not commonly used terms in the context of monitoring business success, making KPIs the correct answer.

A regression analysis is a statistical technique used to determine the relationship between a dependent variable and one or more independent variables. It involves analyzing the statistical significance of the coefficients to understand the impact of the independent variables on the dependent variable. Therefore, if you were to perform a regression analysis, you would require a statistical data warehouse tool that can handle the analysis and provide the necessary statistical calculations and outputs.

Concurrency control facilities ensure the validity of database updates when multiple users attempt to access and change the same information. These facilities help in managing the simultaneous access and modification of data by multiple users, preventing conflicts and maintaining data integrity. They ensure that only one user can make changes to a particular piece of data at a time, thereby avoiding data inconsistencies and ensuring the accuracy and reliability of the database.

Spreadsheets require that you know the physical location of information before you are able to access it. In spreadsheets, data is organized in rows and columns, and each cell has a specific address or location. To access or retrieve data from a spreadsheet, you need to know the specific cell or range of cells where the information is located. This is different from other applications like CRM or ERP, where data is typically stored in a database and can be accessed through queries or search functions without the need to know the physical location.

OLAP (Online Analytical Processing) is the correct answer because it supports the manipulation of information to support decision making. OLAP allows users to analyze large amounts of data from various perspectives and dimensions, enabling them to make informed decisions based on the insights gained. It provides advanced data analysis capabilities such as multidimensional data modeling, data mining, and forecasting, which are essential for decision-making processes.

Data administration is the correct answer because it involves planning for, overseeing the development of, and monitoring the information resource of an organization. This function ensures that the organization's data is properly managed, organized, and utilized to support its goals and objectives. It involves tasks such as data governance, data quality management, data security, and data lifecycle management. Data administration plays a crucial role in ensuring the effective and efficient use of data within an organization.

If you were able to quickly pull information from student records with course records to build students' schedules, you would be using a query-by-example tool. This tool allows users to retrieve data from a database by specifying examples or templates of the desired information. In this scenario, the tool would allow the user to input specific criteria or examples of student records and course records to generate schedules for the students.

Databases that support OLTP (Online Transaction Processing) are commonly known as operational databases. These databases are designed to handle real-time transactional operations, such as inserting, updating, and deleting data. They are optimized for high-speed data processing and are typically used in day-to-day business operations where quick and frequent data access is required. OLAP (Online Analytical Processing) databases, on the other hand, are used for complex data analysis and reporting purposes. Data warehouses are large repositories of data that are used for decision-making and analytics. Relational databases are a type of database management system that organizes data into tables with predefined relationships.

A data mart is a subset of a data warehouse that contains a focused portion of the data warehouse information. It is designed to serve the needs of a specific group or department within an organization. By keeping only relevant and necessary data in the data mart, it allows for easier and faster access to information for analysis and decision-making purposes. This helps to improve efficiency and effectiveness in addressing specific business requirements.

Data administration and database administration have distinct focuses. Data administration is concerned with strategic management, which involves setting policies, standards, and guidelines for the use and management of data within an organization. On the other hand, database administration deals with operational issues, such as ensuring the availability, performance, and security of the database system. These two roles complement each other in effectively managing and utilizing data within an organization.

Information sharing is the term used to describe the use and distribution of information regardless of title or department. It refers to the practice of sharing information among individuals and departments within an organization, as well as with external stakeholders. This allows for the free flow of information, promoting collaboration, transparency, and efficiency. By sharing information, organizations can harness the collective knowledge and expertise of their employees, leading to better decision-making and problem-solving.

SQL (Structured Query Language) is a standardized fourth generation language found in most DBMSs (Database Management Systems). It is used for managing and manipulating relational databases. SQL allows users to create, modify, and retrieve data from databases. It provides a set of commands and syntax for performing various operations such as querying, inserting, updating, and deleting data. Being a standardized language, SQL is widely supported by different database systems, making it a common language for interacting with databases.

A logical view of a database refers to the way in which data is organized and presented to users. It focuses on the conceptual representation of data, allowing users to see only the information they need in a format that is meaningful to them. This view abstracts the underlying physical structure of the database and provides a simplified and user-friendly interface for accessing and manipulating data. Therefore, if you can see only the necessary information in the desired format, it indicates that you are looking at a logical view of the database.

Online transaction processing (OLTP) is the correct answer because it involves the gathering of input information, processing that information, and updating existing information to reflect the gathered and processed information. OLTP systems are designed for real-time transaction processing, such as recording sales, processing orders, or updating customer information. These systems are optimized for high-speed data entry and retrieval, ensuring that transactions are processed quickly and accurately. OLTP is commonly used in applications like banking, e-commerce, and inventory management, where real-time data processing is essential for business operations.

A programmer would see the physical view of the database if they needed to view information as it is stored. The physical view represents how the data is actually stored on the disk, including the file structure, data organization, and storage details. It provides a low-level perspective of the database, allowing programmers to understand and work with the underlying storage structure. This view is important for tasks such as optimizing performance, managing disk space, and troubleshooting issues related to the physical storage of the data.

If the file containing the student information appears in two different places with two different birth dates, it indicates that there may be inconsistencies or errors in the data. In this context, the term "clean" refers to data that is accurate, consistent, and free from any discrepancies or anomalies. Therefore, if the data is not clean, it cannot be considered reliable or trustworthy.

A data warehouse is a logical collection of information used to create business intelligence. This means that it is not a physical hardware environment or an operational database system. Instead, it is a centralized repository where data from various sources is stored, organized, and transformed into a format that is optimized for reporting and analysis. The purpose of a data warehouse is to provide a unified view of data from different systems and enable organizations to gain insights and make informed decisions based on that data.

Query-by-example tools allow users to graphically design the answer to their business questions. These tools provide a user-friendly interface where users can specify their criteria and conditions using a graphical representation, rather than writing complex queries or code. This makes it easier for non-technical users to manipulate and analyze data, as they can visually design their queries and see the results in real-time. Query-by-example tools are commonly used in business intelligence and data analysis to quickly and efficiently retrieve and analyze data.

A data dictionary is a part of a relational database that contains the logical structure for the information. It serves as a repository for metadata, providing information about the database such as the names, definitions, and relationships of the tables, columns, and constraints. The data dictionary helps in maintaining data integrity, ensuring that the database remains consistent and accurate. It is used by database administrators, developers, and users to understand the structure and organization of the database, making it an essential component for managing and accessing data effectively.

A multidimensional data warehouse refers to the structure of the files stored in the warehouse, which contain several layers of columns and rows. This means that the data is organized in a way that allows for analysis and reporting across multiple dimensions, such as time, geography, and product categories. This structure enables users to easily navigate and explore the data from different perspectives, facilitating complex queries and generating meaningful insights.

Report generators are data manipulation tools that allow users to quickly define the formats of needed business reports from information stored in a database. These tools provide a user-friendly interface that allows users to easily select the desired data fields, apply filters, and customize the layout and formatting of the reports. With report generators, users can generate reports that meet their specific business requirements without the need for complex coding or SQL queries.

Reorganization facilities in a DBMS continually maintain statistics concerning how the DBMS engine physically accesses information. These facilities are responsible for optimizing the physical storage and layout of data in the database, ensuring efficient access and retrieval. By monitoring and analyzing the access patterns and performance of the database engine, reorganization facilities can make recommendations for restructuring the data to improve overall system performance. This includes tasks such as reorganizing indexes, redistributing data, and optimizing storage allocation.

Data warehouses exist to support OLAP (Online Analytical Processing). OLAP is a type of software that enables users to analyze multidimensional data from different perspectives. It allows for complex queries and aggregations, making it ideal for decision-making and business intelligence purposes. On the other hand, OLTP (Online Transaction Processing) is a type of software that supports transaction-oriented applications, such as order processing and inventory management. While data warehouses may interact with OLTP systems to extract data, their main purpose is to store and organize data for OLAP analysis. Therefore, OLTP is the correct answer.