Ch 3. Database systems, data centers, and business intelligence

• Database: is an organised collection of data

• Database management system (DBMS):

  • Group of programs that manipulate the database
  • Provide an interface between the database and its users and application programs

• Database administer (DBA): skilled IS professional who directs all activities related to an organisations database

  • An organisation could not complete business activities successfully without data & the ability to process data. Data consists of raw facts, must be organised in a meaningful way

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• Hierarchy of data:

  1. Bit (binary digit): circuit that is either on/off

  2. Byte: made up of 8 bits

  3. Character: building block of info

  4. Field : name/number/combo of characters that describes an aspect of a business object or activity

  5. Record: collection of related data fields

  6. File: collection of related data records

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• Database: collection of integrated and related files

• Entity: General class of people, places, or things (objects) for which data is collected, stored, and maintained

• Attribute: Characteristic of an entity

• Data item: Specific value of an attribute

  • Key field is the employee number. Attribute includes everything else.

• Key: field or set of fields in a record that is used to identify the record

• Primary key: field or set of fields that uniquely identifies the record

  

  

• Approaches to Data Management:

  • Traditional: each distinct operational system used data files dedicated to that system
  • Database approach: pool of related data is shared by multiple application programs

• Some advantages of Database Approach:

  • Improved strategic use of corporate data
  • Reduced data redundancy
  • Easier modification and updating
  • Data and program independence
  • Better access to data and info: (users give simple commands)
  • Better protection of data: (security codes)

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• Disadvantages of Database Approach:

  • More complex
  • Difficult to recover from a failure
  • More expensive

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• When building a database, an organisation must consider:

  • Content: (what is the data collected?)
  • Access: (what data should be provided to which users and when?)
  • Logical structure: (how should data be arranged to make sense?)
  • Physical organisation: (where should data be physically located?)

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• Data Center: Is a climate controlled building or set of buildings that house database servers and the systems that deliver mission-critical information and services.

  • Traditional data centres: Consist of warehouses filled with row upon row of server racks and powerful cooling systems

• Data Modelling: Building a database requires two types of designs:

  • Logical design: abstract model of how data should be structured and arranged to meet an organisation’s information needs
  • Physical design: starts from the logical database and fine-tunes it for performance and cost considerations

• Planned data redundancy: Done to improve system performance to that user reports or queries can be created more quickly

• Data model: is a diagram of data entities and their relationships

  • Enterprise data modelling: investigates the general data and information needs of an organisation at the strategic level

• Entity-relationship (ER) diagrams: data models that use basic graphical symbols to show the organisation of and relationships between data

• An entity-relationship (ER) diagram for a customer order database: development of ER diagrams helps ensure that the logical structure of application programs is consistent with the data relationships in the database

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• The Relational Database Model: Relational Model:

  • describes data using a standard tabular format, each row of a table represents a data entity (record), columns of the table represent attributes (fields).
  • Domain: allowable values for data attributes In the relational model, all data elements are placed in two-dimensional tables, or relations. As long as they share at least one common element, these relations can be linked to output useful information Manipulating data
  • Selecting: eliminates rows according to certain criteria
  • Projecting: eliminates column in a table
  • Joining: combines two or more tables
  • Linking: manipulating two or more tables that share at least one common data attribute
  • When looking for information, one needs three tables: project, department, and manager. Every table leads to another, the information is all connected.

  

• Database Management Systems: Creating and implementing the right database system: (ensure that the database will support both business activities and goals)Capabilities and types of database systems vary considerably

• Database types:

  • Flat file: simple database program whose records have no relationship to one another
  • Single user: only one person can use the database at a time (ex: access, filemaker pro, and infopath)
  • Multiple users: allows dozens or hundreds of people to access the same database system at the same time (ex: oracle, sybase, and IBM)

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• Schema: used to describe the entire database

• DBMS: can reference a schema to find where to access the requested data in relation to another piece of data

• Data definition language (DDL): collection of instructions and commands used to define and describe data and relationships in a specific database. Allows database’s creator to describe data and relationships that are to be contained in the schema

• Data dictionary: detailed description of all data used in the database

  • Storing and retrieving data: when an application program needs data, it requests it through the DBMS

• Concurrency control: method of dealing with a situation in which two or more users or applications need to access the same record at the same time

  • Logical & physical access paths: Manipulating data and generating reports

• Data manipulation language (DML): commands that manipulate the data in a database

• Structured query language (SQL) standard query language for relational databases

  • Once a database has been set up and loaded with data: it can produce reports, documents, and other outputs

• Database administration (DBA): works with users to decide the content of the database

  • Works with programmers as they build applications to ensure that their programs comply with database management system standards and conventions

• Data administrator: Responsible for defining and implementing consistent principles for a variety of data issues

  • Popular database management systems:

  

• DBMSs can act as front-end or back-end applications:

  • Front-end applications interact directly with people
  • Back-end applications interact with other programs or applications

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• Linking database to the internet:

  • Semantic web: developing a seamless integration of traditional databases with the internet
  • Provides metadata with all web content using technology called the resource description framework (RDF)

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• Data warehouse: database that holds business information from many sources in the enterprise

• Data mart: subset of a data warehouse

• Data mining: information-analysis tool involves the automated discovery of patterns and relationships in a data warehouse

  • Elements of Data Warehouse:

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• Predictive analysis: form of data mining that combines historical data with assumptions about future conditions to predict outcomes of events

• Used by retailers to upgrade occasional customers into frequent purchasers

• Software can be used to analyse a company’s customer list an a year’s worth of sales data to find new market segments

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• Common data mining applications:

  • customer churn
  • direct marketing
  • fraud detection
  • market basket analysis
  • market segmentation
  • trend analysis

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• Business intelligence:

  • Involves gathering enough of the right information in a timely manner and usable form and analysing it to have a positive impact on business strategy, tactics, or operations
  • Competitive intelligence: limited to information about competitors and the ways that knowledge affects strategy, tactics, and operations
  • Counterintelligence: steps organisation takes to protect information sought by “hostile” intelligence gatherers
  • Data loss prevention (DLP):
  • Refers to systems designed with government to lock down data within an organisations
  • Powerful tool for counterintelligence
  • A necessity in complying with government regulations that require companies to safeguard private customer data

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• Distributed database:

  • Database in which the data may be spread across several smaller databases connected via tele-communications devices
  • Gives corporations more flexibility in how databases are organised and used

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• Replicated database:

  • Holds a duplicate set of frequently used data
  • Telecommunications systems link the computers so that users at all locations can access the same distributed database, no matter where the data is actually stored

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• Online analytical processing (OLAP): software that allows users to explore data from a number of different perspectives

  • Provides top-down, query-driven data analysis
  • Requires repetitive testing of user-originated theories
  • Requires a great deal of human ingenuity and interaction with the database to find information

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• Object-oriented database:

  • Stores both data and its processing instructions
  • Uses an object-oriented database management system (OODBMS) to provide a user interface and connections to other programs

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• Object-relational database management system (ORDBMS):

  • Provides the ability for third parties to add new data types and operations to the database

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• Visual databases: can be stored in some object-relational databases pr special purpose database systems

• Virtual database systems: allow different databases to work together as a unified database systems

• **Spatial data technology:**using database to store and access data according to the locations it describes \n

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