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Explain the four primary traits that determine the value of information. PowerPoint Presentation
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Explain the four primary traits that determine the value of information.

Explain the four primary traits that determine the value of information.

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Explain the four primary traits that determine the value of information.

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  1. CHAPTER 6: LEARNING OUTCOMES • Explain the four primary traits that determine the value of information. • Describe a database, a database management system, and the relational database model. • Identify the business advantages of a relational database. • Explain the business benefits of a data-driven website. • Define a data warehouse and provide a few reasons it can make a manager more effective. • Explain ETL and the role of a data mart in business. • Define data mining and explain the three common forms for mining structured and unstructured data. • Identify the advantages of using business intelligence to support managerial decision making.

  2. THE BUSINESS BENEFITS OF HIGH-QUALITY INFORMATION • Successfully collecting, compiling, sorting, and analyzing information can provide tremendous insight into how an organization is performing • Information Type: Transactional and Analytical • Transactional Information—Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks • Analytical Information—Encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks

  3. THE BUSINESS BENEFITS OF HIGH-QUALITY INFORMATION • Information Timeliness • Real-time Information—Immediate, up-to-date information • Real-time System—Provides real-time information in response to requests. • Information Quality • Common characteristics of high-quality information: • Accurate, Complete, Consistent, Unique, and Timely • Information Governance • Data governance

  4. STORING INFORMATION IN A RELATIONAL DATABASE MANAGEMENT SYSTEM • Database—Maintains information about various types of objects, events, people, and places • Database Management Systems (DBMS)—Allows users to create, read, update, and delete data in a relational database • Data Element—The smallest or basic unit of information • Data Model—Logical data structures that detail the relationships among data elements using graphics or pictures • Metadata—Provides details about data • Data Dictionary—Compiles all of the metadata about the data elements in the data model

  5. STORING INFORMATION IN A RELATIONAL DATABASE MANAGEMENT SYSTEM • Storing Data Elements in Entities and Attributes • Entity—A person, place, thing, transaction, or event about which information is stored • Attribute—The data elements associated with an entity • Record—A collection of related data elements • Creating Relationships Through Keys • Primary Key—A field (or group of fields) that uniquely identifies a given entity in a table • Foreign Key—A primary key of one table that appears an attribute in another table and acts to provide a logical relationship among the two tables

  6. USING A RELATIONAL DATABASE FOR BUSINESS ADVANTAGES • Increased Flexibility • A database needs to handle changes quickly and easily, just as any business needs to be able to do • Physical View—Deals with the physical storage of information on a storage device • Logical View—Focuses on how individual users logically access information to meet their own particular business needs • Increased Scalability and Performance • Scalability—Refers to how well a system can adapt to increased demands • Performance—Measures how quickly a system performs a certain process or transaction

  7. USING A RELATIONAL DATABASE FOR BUSINESS ADVANTAGES • Reduced Data Redundancy • Data Redundancy—The duplication of data or storing the same information in multiple places • Inconsistency is one of the primary problems with redundant information • Increased Information Integrity (Quality) • Information Integrity—Measures the quality of information • Integrity Constraint—Rules that help ensure the quality of information • Relational integrity constraint • Business-critical integrity constraint

  8. USING A RELATIONAL DATABASE FOR BUSINESS ADVANTAGES • Increased Information Security • Information is an organizational asset and must be protected • Databases offer several security features: • Password—Provides authentication of the user • AccessLevel—Determines who has access to the different types of information • AccessControl—Determines types of user access, such as read-only access

  9. DRIVING WEBSITES WITH DATA • Data-Driven Websites—An interactive website kept constantly updated and relevant to the needs of its customers using a database • Data-driven website advantages: • Easy to manage content • Easy to store large amounts of data • Easy to eliminate human errors

  10. THE BUSINESS BENEFITS OF DATA WAREHOUSING • Data warehouses extend the transformation of data into information • The data warehouse provided the ability to support decision making without disrupting the day-to-day operations • Data Warehouse—A logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks • The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes

  11. PERFORMING BUSINESS ANALYSIS WITH DATA MARTS • Extraction, Transformation, and Loading (ETL)—A process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse • Multidimensional Analysis • Dimension—A particular attribute of information • Cube—Common term for the representation of multidimensional information • Information Cleansing or Scrubbing—A process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information

  12. UNCOVERING TRENDS AND PATTERNS WITH DATA MINING • Data Mining—The process of analyzing data to extract information not offered by the raw data alone • Data-mining Tools—Use a variety of techniques to find patterns and relationships in large volumes of information • Structured Data—Data already in a database or a spreadsheet • Unstructured Data—Data does not exist in a fixed location and can include text documents, PDFs, voice messages, emails • Text Mining—Analyzes unstructured data to find trends and patterns in words and sentences • Web Mining—Analyzes unstructured data associated with websites to identify consumer behavior and website navigation

  13. UNCOVERING TRENDS AND PATTERNS WITH DATA MINING • Cluster Analysis—A technique used to divide an information set into mutually exclusive groups • Association Detection—Reveals the relationship between variables along with the nature and frequency of the relationships • Market Basket Analysis • Statistical Analysis—Performs such functions as information correlations, distributions, calculations, and variance analysis • Forecast and Time-Series Information

  14. SUPPORTING DECISIONS WITH BUSINESS INTELLIGENCE • The Problem: Data Rich, Information Poor • Businesses face a data explosion as digital images, email in-boxes, and broadband connections doubles every year • The Solution: Business Intelligence • BI enables business users to receive data for analysis that is: • Reliable • Consistent • Understandable • Easily Manipulated