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Chapter 11 Computers.docx

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Computing and Information Science
CIS 1200
John Saville

Chapter 11 Chapter Objectives (pg. 508) What is a database, and why is it beneficial to use databases? (pp. 510 – 511) Databases are electronic collections of related data that can be organized so that it is more easily accessed and manipulated. Properly designed databases cut down on data redundancy and duplicate data by ensuring relevant data is recorded in only one place. This also helps eliminate data inconsistency, which comes from having different data about the same transaction recorded in two different places. When databases are used, multiple users can share and access information at the same time. Databases are used any time complex information needs to be organized or more than one person needs to access it. In these cases, lists (which are used to keep track of simple information) are no longer efficient. What components make up a database? (pp. 512 – 525) The three main components of a database are: 1. Fields: A database stores ach category of information in a field, which is usually displayed in a column (e.g., name) 2. Records: A group of related fields (e.g., name + address + phone) 3. Tables: A group of related records (e.g., all student records) A category of information in a database is stored in a field. Each field is identified by a field name, which is a way of describing the field. Fields are assigned a data type that indicates what type of data can be stored in the field. Common data types include:  Text field: holds any combination of alphanumeric data  Numeric field: hold numbers that can be used to perform calculations  Computational field: a field that stores the contents of a calculation  Date field: holds calendar dates  Memo field: like a text field, but for long pieces of text  Object field: holds items like pictures, videos or documents  Hyperlink field: hold hyperlinks to Web pages To keep records distinct, each record must have one field that has a value unique to that record. This unique field is a primary key (or a key field). What types of databases are there? (pp. 516 – 517) The three major types of databases currently in use are: 1. Relational  Relational databases are characterized by two-dimensional tables of data in which a common field is maintained in each of two tables and the information in the tables is linked by this field. 2. Object-oriented  Object-oriented databases store data in objects, not in tables. The objects also contain instructions about how the data is to be manipulated or processed. 3. Multidimensional  Multidimensional databases represent data in three- dimensional cubes to enable faster retrieval of information from the database. What do database management systems do? (pp. 517 – 526) Database management systems (DBMSs) are specially designed applications (such as Oracle or Microsoft Access) that interact with the user, other applications, and the database itself to capture and analyze data. The main operations of a DBMS are: 1. Creating databases  Defining the data to be captured by describing it in a “data dictionary” that defines the name, data type and length of each field in the database. 2. Entering data  Inputting the data into the database fields. Data is validated by field constraints, which are properties that must be satisfied for an entry to be accepted into a field o Range check: ensures that data falls within a certain range of numbers o Field constraint: a property that must be satisfied for an entry to be accepted into the field o Completeness check: a field that is required to have data in it o Consistency check: compares the value of data in two or more fields to see if these values are reasonable o Alphabetic check: confirms that only textual characters are entered in a field o Numeric check: confirms that only numbers are entered in a field 3. Viewing (or browsing) data  Displaying the tables on screen, often with a variety of viewing options 4. Sorting (or indexing) data  Organizing the displayed data by a certain field (column) in either ascending or descending order 5. Extracting (or querying) data  Requesting specific records to be viewed in a query language (such as SQL)  e.g., requesting records for all students with a date of birth between 1990 – 1991) 6. Outputting data  Printable electronic reports (such as a summary of today’s sales transactions) or exporting data to other applications A query language is used to extract records from a database. Almost all relational databases today use structured query language, or SQL. However, most DBMSs include wizards that enable you to query the database without learning a query language. The most common form of output for any database is a printed report. How do relational databases organize and manipulate data? (pp. 526 – 532) Relational databases operate by organizing data into various tables based on logical groupings. Because not all of the data in a relational database is stored in the same table, a methodology must be implemented to link data between tables. In relational databases, the links between tables that define how the data is related are referred to as relationships. To establish a relationship between two tables, both tables must have a common field (or column). Once linked, information can be drawn from multiple tables through the use of queries (for onscreen viewing of data) or report generators (used to produce printed reports). What are data warehouses and data marts, and how are they used? (pp. 532 – 536) A data warehouse is a large-scale electronic repository of data that contains and organizes in one place all the relevant data related to an organization. Data warehouses often contain information from multiple databases. Because it can be difficult to find information in a large data warehouse, small slices of the data warehouse called data marts are often created. The information in data marts pertains to a single department within the organization, for example. Data warehouses and data marts consolidate information from a wide variety of sources to provide comprehensive pictures of operations or transactions within a business. Figure 11.28 Data from individual databases is drawn together under appropriate subject headings in a data warehouse. Managers can then produce comprehensive reports that would be impossible to create from the individual databases. Figure 11.29 An overview of the data warehouse process. What is an information system, and what types of information systems are used in business? (pp. 536 – 541) Information systems are software-based solutions that are used to gather and analyze information. Information systems fall into one of five categories. 1. Office support system (OSS)  designed to assist employees in accomplishing their day-to-day tasks and improve communications 2. Transaction processing system (TPS)  a system that is used to keep track of everyday business activities 3. Management information system (MIS)  provides timely and accurate information that enables managers to make critical business decisions 4. Decision support system (DSS)  a system designed to help managers develop solutions for specific problems 5. Enterprise resource planning (ERP) system  a large software system that gathers information from all parts of a business and integrates it to make it readily available for decision making. What is data mining, and how does it work? (pp. 542 – 543) Data mining is the process by which large amounts of data are analyzed to spot otherwise hidden trends. Through data mining processes, data is organized so that it provides meaningful information that can be used by managers to identify business trends. Common data mining processes are: 1. Classification  Managers define data classes that they think will be helpful in spotting trends and then apply these class definitions to all unclassified data to prepare it for analysis. 2. Estimation  Managers assign a value to data based on some criterion.  E.g., bank running customer data through a program that assigns them a score based on certain records (such as income) to estimate which customers would be likely to be granted a credit card. 3. Affinity grouping  Applying association rules to data to group data together  E.g., identifying that 2 items are bought together 70% of the time. 4. Clustering  Allowing data-mining software to organize data into similar subgroups. A manager then determines whether the identified clusters are meaningful. 5. Description (visualization)  Describing data in order that managers can visualize it. Key Terms Alphabetic Check: Confirms
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