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CSI315 PowerPoint Presentation

CSI315

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CSI315

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  1. CSI315 Web Development Technologies Continued

  2. Data • Data is an un-processed collection or representation of raw facts, concepts, or instructions in a manner suitable for communication, interpretation, or processing by humans or by automatic means. It can be defined as unprocessed information. • Data that has been interpreted, translated, or transformed to reveal the underlying meaning is called information. Information is the result of processing, manipulating and organizing data in a way that adds to the knowledge of the person receiving • Data is converted into information, and information is converted into knowledge.

  3. The Data Layer • All of the web technologies at the Data Layer define, describe, or standardize one or more of the data characteristics: • Data types (letters, numbers, dates, ints, floats. strings ) • Data descriptions (reference keywords) • Data formats (DD/MM/YYYY, $ ) • Data values Data is stored in databases across the Internet

  4. The Database • A logical collection of interrelated data organized to meet the needs and structure of an organization. • A collection of information organized and presented to serve a specific purpose. A computerized database is an updated, organized file of machine readable information that is rapidly searched and retrieved by computer. • A collection of related electronic records in a standardized format, searchable in a variety of ways, such as title, author, subject, and keyword.

  5. Databases • Databases are designed to offer an organized mechanism for storing, managing and retrieving information. • Data from the database extracted from the internal (Finance, Marketing, Production, Personnel etc.) and external sources like industry data, regional employment data etc. • Data may organized in one or more separate databases or in a data warehouse, or a special independent database.

  6. Database Actions Actions that you can perform to a database • Retrieve all records that match certain criteria • Update records in bulk • Cross-reference records in different tables • Perform complex aggregate calculations

  7. Database Management System (DBMS) A collection of computer programs that allow creation, storage, modification, and extraction of information from the database. • Captures data for inclusion in the database • Updates(adds, deletes, edits, changes) data records and files • Interrelates data from different sources • Retrieves data from the database for queries and reports • Provides comprehensive data security-access, recovery • Performs complex data manipulation tasks based on queries • Tracks data within the DSS • Manages data through a data dictionary

  8. The Query Facility Performs queries on the data • It accepts data from other DSS components • Determines how the request can be filled ( consults data dictionary) • Formulates the detailed request • Returns the results to the issuer of request

  9. Data Directory • A catalog of of all data in the database • Contains data item definitions, their sources and exact meaning • Supports updates like additions and deletions

  10. Web Databases(OLAP) • Analytic databases (a.k.a. OLAP- On Line Analytical Processing) are primarily static, read-only databases which store archived, historical data used for analysis . • They enable analysts, managers and executives to gain insight into data through fast, consistent, interactive access. For example a user could • request spreadsheet analysis showing all of a company's products sold in a certain month • compare revenue figures with those for the same products another month • see a comparison of other product sales in another branch/company in the same time period

  11. Web Databases (OLTP) • Operational databases (a.k.a. OLTP On Line Transaction Processing • Databases that allow the real-time processing of SQL transactions to support e-commerce and other time-critical applications. This type of processing is known as online transaction processing (OLTP ) • An OLTP database has Read and Write access. This is where transactions are actually entered, modified, and/or deleted.

  12. Data model • A data model is a "description" of both a container for data and a methodology for storing and retrieving data from that container. • Data models are abstractions, often at times mathematical algorithms and concepts • Used for presenting entities of interest and their relationships in the database

  13. Database Models Relational Database : • most popular form. Table = data file • Data collected in 2-dimensional tabular form. Columns(field) e.g Data field called Cu. Name ,ID, Address etc. ), rows (records made up of several field) • Data files may be related by a common field forming a relation.

  14. Hierarchical Databases Data items arranged in a top down fashion • Logical links between data items e.g

  15. Database Models Cntd. Networked Databases • Structure allows dependencies among elements • Saves storage space through sharing of data items

  16. Database Models Cntd O-O Databases • Defines data as objectsandmodels natural relationships between objects(inheritance, encapsulation, behavior etc.) • Uses a hierarchy of classes and sub-subclasses Multimedia based databases Uses a variety of formats in addition to text and numeric fields (bitmaps,video clips, sound, virtual reality)

  17. Database Connectivity two ways • connecting to the database directly using a command shell • connecting to the database over the network using sockets (if that database allows such interaction).

  18. Database Issues: Online Database: A collection of information organized in such a way that a website visitor can quickly select desired pieces of data. Uses include: • Show visitors your vast inventory by price, category and pictures. • Let customers use a search function to quickly find a product or service. • A must for e-commerce websites that carry 10 or more items. • Quickly change and update your website through the administration tool of the website. • Store information.

  19. Database Issues (Tutorial) • Data warehousing • Data mining