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Types of Data

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elon
18 diapositives · 783 Views · Jul 31, 2014

Types of Data. Predefined Data Items: Numerical/alphabetical items whose meaning and format are specified explicitly. Common in transaction oriented systems Text: A series of characters; meaning is not important Images Audio Video. Logical Vs Physical Views of Data.

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Types of Data
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  1. Types of Data • Predefined Data Items: • Numerical/alphabetical items whose meaning and format are specified explicitly. • Common in transaction oriented systems • Text: • A series of characters; meaning is not important • Images • Audio • Video

  2. Logical Vs Physical Views of Data • A logical view of data expresses the way a user thinks about the data • Usually expressed in terms of a data model. • A physical view of data is the way computers handle the data, i.e., the storage and retrieval of it. • Usually stated in terms of specific locations on storage devices plus techniques used to access it

  3. Data Access Methods • Sequential Access: Individual records within a file are processed in sequence. • Direct Access: The individual item in the file is accessed directly. • Indexed Access: Uses a table(index) to locate the required piece of data. • Often called ISAM(Indexed Sequential Access Method)

  4. Transaction Processing • Logical Reference: Identifies the data that a programmer wants but does not specify how to find the data. • Record Locking: The ability to lock the specific record temporarily to prevent access by any other process until it is unlocked.

  5. Distributed Databases • Databases, parts of which exist in different locations. • Two Phase Commit: A technique used to maintain consistency across the databases. • Database Replication is a common alternative to distributed databases.

  6. Tradeoffs Between Centralized and Distributed Architectures • Cost of data transmission. • Costs of synchronizing distributed parts of the database. • Degree to which the entire database must be current at all times.

  7. Data Warehouse • A large database that is a collection of data from smaller databases. • Used to support decision making. • Updated less frequently than say for example transaction databases. • Supports fast online queries and quick summaries for managers.

  8. Data Warehouse (Contd.) • Global in view. • Data mart is a subset of a data warehouse that provides data about a specific function or a department. • Can “drill down” into several layers of data to locate a problem or an opportunity • Queries are often multidimensional in nature.

  9. Capabilities a good DBMS must possess • Controlling Redundancy • Problems with redundancy: • Need for single logical update • Waste of storage space • Inconsistency • Restricting Unauthorized Access • Provide a security and authorization subsystem

  10. Capabilities a good DBMS must possess • Persistent Storage for Program Objects and Data Structures • Persistent Objects: Survive the termination of program execution and can later be directly retrieved. • Cause of emergence of object-oriented DBMS. • Database Inferencing Using Deduction Rules (called deductive database systems)

  11. Capabilities a good DBMS must possess • Providing Multiple User Interfaces. • Representing Complex Relationships among Data. • Enforcing Integrity Constraints • Specifying data type for each data item. • Specifying that records in one file must be related to records in other files. • Providing Backup and Recovery.

  12. Implications of the Database Approach • Potential for Enforcing Standards • Reduced Application Development Time • Flexibility • Availability of Up-to-Date Information • Economies of Scale

  13. Factors Related to Information Usefulness • Information Quality • Information Accessibility • Information Presentation

  14. Issues Related to Information Quality • Accuracy: The extent to which the information represents what it is supposed to represent • Precision: Fineness of detail in the portrayal • Completeness: Extent to which the available information is adequate for the task

  15. Issues Related to Information Quality • Age: Amount of time that has passed since the data were produced. • Timeliness: Extent to which the age of the data is appropriate for the task and the user • Source: The person or organization that produced the data

  16. Issues Related to Information Accessibility • Availability: Extent to which the necessary information exists and can be accessed effectively by people who need it • Admissibility: Whether or not use of the information is legal or culturally appropriate in this situation

  17. Issues Related to Information Presentation • Level of Summarization: Comparison between number of items in the original data and number of items displayed. • Format: Form in which information is displayed to the user.

  18. Issues Related to Information Security • Access Restriction: Procedures and techniques controlling who can access what information under what circumstances. • Encryption: Converting data to a coded from that unauthorized users cannot decode