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Agricultural to Industrial to Information Age

Learn about data processing history, database structures, terminology, DBMS solutions, data life cycle, and everyday applications of DBMS. Understand database objects, user roles, and advantages of database processing.

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Agricultural to Industrial to Information Age

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  1. Agricultural to Industrial to Information Age • Data • Bits and Bytes • e.g. 5184424028 • Information • organized and presented in a form suitable for decision making • e.g. (518)442-4028 • Knowledge

  2. Desirable Attributes of Information • Shareable • Transportable • Secure • Accurate • Timely • Relevant

  3. Where do companies get information from? • They buy it • Consultants, publications, news services etc. • They generate it • Computer systems (programs process data stored in databases) • Employees (apply experience and intelligence)

  4. Where do we store Intangible Assets -- Information? • In people’s heads • On paper • In card-files • In computers

  5. Entities, Attributes, and Relationships • Entity – a person, place, thing, or event • Attribute – a property of an entity • For the entity “Person,” attributes could include eye color and height • Relationship – an association between entities • Publishers are related to the books they publish, and a book is related to its publisher

  6. Terminology • Fields - attribute • Domain -Description of allowed values for an attribute • Records - logically connected set of one or more fields. • Files - collection of records

  7. History of Data Processing • Manual record-keeping • High labor costs and human errors • Data file – stores information on a single entity and the attributes of that entity • Database – a structure that can store information about multiple types of entities, the attributes of these entities, and the relationships among the entities

  8. Limitations of File-Based Systems • Separation and Isolation of Data • Duplication of Data • Data dependence • Incompatibility of files • Fixed queries / proliferation of application programs / pressure on DP staff

  9. Database • A self-describing collection of integrated records • Properties of a Database: • It represents some aspect of the real world • It is a logically coherent collection of data with some inherent meaning • It is designed, built, and populated with data for a specific purpose • It has users and applications

  10. Spreadsheet or Database? • Data size • Data storage format • Data structure • extent to which relationships among data items are fixed • Data sharing • Data control • degree of data input editing and validating

  11. High Low Static Dynamic Structure Low High Low High Sharing High Low High Low High Low Control Spreadsheet DB Database Either SOLUTION

  12. DBMS • A software system that : • Enables users to define, create and maintain the database • Provides controlled access to this database

  13. DBMS components • Machine • Hardware • Software • Data • Human • Procedures • People

  14. Data Life Cycle • Data acquisition • data modeling and populating with ultimate goal of storing data • Data use • Combines data that has been previously stored and interprets output in a decision making context (Data Warehousing)

  15. Data acquisition • Logical database design • E/R diagrams, normalization, database models • Physical database design • Integrity constraints, indexes, denormalization • Populating the database • data entry, import, download • Update records • data dictionary, metadata

  16. Data Use • Define view • Query design, DDL (SQL or QBE) • Retrieve data • Query performance and optimization, concurrency controls • Manipulate data • Sort, aggregate, classify, analyze • Present results • Reports, forms

  17. Access Database Objects • Tables • Stores data as records • Queries • Answers questions about the database • Forms • Presents data using a customized layout • Reports • Formats the data (primarily for printouts) • Macros • Used to automate repetitive tasks • Modules • Pages

  18. Users • Administrators • Data Administrator • Database Administrator • Database designers • Conceptual and logical design (WHAT?) • Physical design (HOW?) • Application programmers • End users • naïve (e.g checkout assistant) • sophisticated

  19. Everyday Database Systems • Supermarket • Credit card • Travel Agent • Insurance • Library • University

  20. Applications of DBMS • Airline reservations systems • Reservations (customer name, assigned seat) • Flights (airports, arrival and departures) • Tickets (prices, requirements, availability) • Banking systems • Customers (names, addresses, accounts, loans) • Corporate records • Accounts (payable, receivable) • Employees (names, addresses, salary, benefits)

  21. Creating a Table in Access • Datasheet view • To add, delete or edit records • Design View • To define table the initially and specify its fields

  22. Custom Tables • Validation rules • Input masks • Default values • Lookup fields • Format

  23. Advantages ofDatabase Processing • Getting more information from the same amount of data • When all the data for various systems are stored in a single database, the information becomes available, as well as the process of retrieving the information can be quick and easy

  24. Advantages ofDatabase Processing • Sharing of data • Several users can have access to the same piece of data (Concurrency control allows shared access) • Balancing conflicting requirements • A person or group, often called Database Administration/Administrator (DBA) can structure the database in such a way that it benefits the entire organization, not just a single group

  25. Advantages ofDatabase Processing • Controlling redundancy • Not only saves space, but makes the updating process easier • Consistency • Consistency is a direct result of redundancy, so by reducing redundancy, there is much less potential for this sort of inconsistency with the database approach

  26. Advantages ofDatabase Processing • Integrity • An integrity constraint is a rule that must be followed by data in the database • Example: Not allowing a person’s age to be lower than zero • Security • The prevention of access to the database by unauthorized users • Recovery control restores the data to previous consistent state after hardware/software failure

  27. Advantages ofDatabase Processing • Increasing productivity • A good DBMS comes with many features that allow users to gain access to data without having to do any programming at all • Data independence • A property that allows the structure of a database to be changed without the programs that access the database having to change

  28. Disadvantages ofDatabase Processing • DBMS size • DBMSs are large programs that occupy a large amount of disk space as well as internal memory • DBMS complexity • The complexity and breadth of the functions provided by a DBMS make it a complex product to use

  29. Disadvantages ofDatabase Processing • Greater impact of a failure • A failure on the part of any one user that damages the database in some way may affect all the other users on the system • More difficult recovery • If the database is being updated by a large number of users, all updates must be redone since the time of its restoration

  30. When can an organization justify a database? • Application needs are constantly changing • Rapid access is required for ad hoc queries • Need to reduce long lead times and high development costs for new systems • Data elements are shared by users • Need to communicate and relate data across functional and departmental boundaries • Need to improve quality of data resources and control access to them

  31. History of DBMS • IBM developed the Generalized Update Access Method (GUAM) in 1964 for North American Rockwell, the prime contractor for the APOLLO project • GUAM was made available for the general public under the name Data Language/I (DL/I) in 1966

  32. History of DBMS • DL/I became the data management component for the Information Management System (IMS), which was the dominant DBMS for many years • In the mid-1960s, General Electric developed Integrated Data Store (I-D-S)

  33. History of DBMS • First generation • Hierarchical and network models • Second generation • Relational models • Third generation • Object oriented models

  34. Data Models • Record Based • Hierarchical (60’s) • Network (70’s) • Relational (80’s) • Object Based • Entity-Relationship (70’s) • Semantic data models (80’s) • Object-oriented (90’s)

  35. Record-Based Data Models • Hierarchical • Parent-child relationships with only one parent (N:1 relationships are not supported) • Network • Extends hierarchical model by allowing multiple parents • Associations are created via pointers • Relational

  36. Hierarchical Model • Perceived by the user as a collection of hierarchies, or trees • More restrictive structure than a network model • GUAM, DL/I, and IMS are examples of DBMSs that conform to the hierarchical model

  37. Network Model • Perceived by the user as a collection of record types and relationships between these record types • I-D-S is an example of a DBMS that conforms to the network data model

  38. Assignment 1 • MS Access 2000 • Pages AC 2.34 –2.36 • #1-16

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