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Data Resource Management
Data Resource Management   A managerial activity   Applies information systems technology to    managing data resources
What is a DataBase?   Database – a collection of related data organized in    a way to facilitate data processing (ie sea...
Foundation Data Concepts   Levels of data       Character           Single alphabetical, numeric, or other symbol     ...
Foundation Data Concepts (continued)    Files (table)        A group of related records        Classified by          ...
Foundation Data Concepts (continued)      Data Elements
Foundation Data Concepts (continued)    Database (wrap up)        Integrated collection of logically related data elemen...
Major Types of Databases                   External                                        Databases on                   ...
Types of Databases   Operational       Supports business processes and operations       Also called subject-area databa...
Types of Databases (continued)    Distributed        Replicated and distributed copies or parts of         databases on ...
Data Warehouse Databases. These store data from current and previous years that has been extracted from the various operat...
   Data Marts. Are subsets of the data included in    a Data Warehouse which focus on specific    aspects of a company, e...
   External Databases. Many organizations make    use of privately generated and owned online    databases or data banks ...
Data Warehouse and Data Mining                                           ClientOperational                                ...
Data Warehouses and Data Mining   Data warehouse       Stores data extracted from operational, external,        or other...
How Organizations Get the Mostfrom Their Data   Data Mining       A method for better understanding data       Informat...
How Organizations Get theMost from Their Data   Data Mining       Online Transaction Processing (OLTP)           Immedi...
How Organizations Get theMost from Their Data   Data Mining       Online Analytical Processing (OLAP)           Graphic...
Applications   Banking: loan/credit card approval       predict good customers based on old customers   Customer relati...
Applications (continued)   Medicine: disease outcome, effectiveness of    treatments       analyze patient disease histo...
Data Mining in Use   Basketball teams use it to track game strategy   Cross Selling   Target Marketing   Holding on to...
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data resource management

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data resource management

  1. 1. Data Resource Management
  2. 2. Data Resource Management A managerial activity Applies information systems technology to managing data resources
  3. 3. What is a DataBase? Database – a collection of related data organized in a way to facilitate data processing (ie searches) DBMS – Database Management Systems  Use a DBMS software to create, store, organize, and retrieve data from a single database or several databases  Example: Microsoft Access
  4. 4. Foundation Data Concepts Levels of data  Character  Single alphabetical, numeric, or other symbol  Field  Groupings of characters  Represents an attribute of some entity  Records  Related fields of data  Collection of attributes that describe an entity  Fixed-length or variable-length
  5. 5. Foundation Data Concepts (continued)  Files (table)  A group of related records  Classified by  Primary use  Type of data  permanence
  6. 6. Foundation Data Concepts (continued)  Data Elements
  7. 7. Foundation Data Concepts (continued)  Database (wrap up)  Integrated collection of logically related data elements  Consolidates records into a common pool of data elements  Data is independent of the application program using them and type of storage device
  8. 8. Major Types of Databases External Databases on the Internet & Online Services Client PC or Distributed NCDatabases on Intranets & Network Operational Databases of Other Server the Organization Networks End User Data Data Databases Warehouse Mart
  9. 9. Types of Databases Operational  Supports business processes and operations  Also called subject-area databases, transaction databases, and production databases.  These also include databases of Internet and electronic commerce activity, such as click stream data or data describing online behavior of visitors at a company’s website.
  10. 10. Types of Databases (continued)  Distributed  Replicated and distributed copies or parts of databases on network servers at a variety of sites.  Done to improve database performance and security  These are the databases of local workgroups and departments at regional offices, branch offices, and other work sites needed to complete the task at hand.
  11. 11. Data Warehouse Databases. These store data from current and previous years that has been extracted from the various operational and management databases of the organization. As a standardized and integrated central source of data, warehouses can be used by managers for pattern processing, where key factors and trends about operations can be identified from the historical record.
  12. 12.  Data Marts. Are subsets of the data included in a Data Warehouse which focus on specific aspects of a company, e.g. department, business process, etc. End User Databases. These consist of a variety of data files developed by end users at their workstations. For example, an end user in sales might combine information on a customer’s order history with her own notes and impressions from face-to-face meetings to improve follow-up.
  13. 13.  External Databases. Many organizations make use of privately generated and owned online databases or data banks that specialize in a particular area of interest. Access is usually through a subscription for continuing links or a one-time fee for a specific piece of information (like the results of a single search). Other sources like those found on the Web are free.
  14. 14. Data Warehouse and Data Mining ClientOperational PC or Analytical NCDatabases Data Data Store Management Enterprise Subsystem WarehouseData Data MartAcquisition Data Access Data AccessSubsystem and Delivery and Delivery Metadata Subsystem Subsystem Metadata Directory ManagementWarehouse Subsystem MetadataDesign Repository Web WebSubsystem Information Information System System
  15. 15. Data Warehouses and Data Mining Data warehouse  Stores data extracted from operational, external, or other databases of an organization  Central source of “structured” data  May be subdivided into data marts
  16. 16. How Organizations Get the Mostfrom Their Data Data Mining  A method for better understanding data  Information on customers, products, markets, etc.  Drill down: from summary to more detailed data  Sort and extract information  Trends, correlations, forecasting, statistics
  17. 17. How Organizations Get theMost from Their Data Data Mining  Online Transaction Processing (OLTP)  Immediate automated responses to user requests  Multiple concurrent transactions  A big part of interactive Internet e-commerce
  18. 18. How Organizations Get theMost from Their Data Data Mining  Online Analytical Processing (OLAP)  Graphical software tools that provide complex analysis of data stored in a database  Drills down to deeper levels of consolidation  Time series and trend analysis  “What if” and “why” questions
  19. 19. Applications Banking: loan/credit card approval  predict good customers based on old customers Customer relationship management:  identify those who are likely to leave for a competitor. Targeted marketing:  identify likely responders to promotions Fraud detection: telecommunications, financial transactions  from an online stream of event identify fraudulent events Manufacturing and production:  automatically adjust knobs when process parameter changes
  20. 20. Applications (continued) Medicine: disease outcome, effectiveness of treatments  analyze patient disease history: find relationship between diseases Molecular/Pharmaceutical: identify new drugs Scientific data analysis:  identify new galaxies by searching for sub clusters Web site/store design and promotion:  find affinity of visitor to pages and modify layout
  21. 21. Data Mining in Use Basketball teams use it to track game strategy Cross Selling Target Marketing Holding on to Good Customers Weeding out Bad Customers

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