Unit 5Organizing Data and Information

Learning OutcomesUnderstand records in a databaseUnderstand components of a DBMSIdentify database models and typesDefine

Database conceptsStructures & record keepingData languagesDevelopment toolsSecurity and admin

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Data ManagementWithout data and the ability to process it, an

organization could not successfully complete most business activities

Data consists of raw factsTo transform data into useful information, it

must first be organized in a meaningful way

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The Hierarchy of DataCharacter: a group of 8bits forming a byte

Can be an uppercase letter, lowercase letter, numeric digit, or special symbol

Field: group of characters, typically a name, number, or combination of characters that describes an aspect of a business object or activity

Record: collection of related data fieldsFile: collection of related recordsDatabase: collection of integrated and related

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The Hierarchy of Data (continued)

5

Figure 5.1: The Hierarchy of Data

DefinitionsDatabase management system (DBMS):

group of tools that support database management and it’d performance in an organisation

Data independence: data is independent from the program that creates it. This means programs and data developed in for 1 app are compatible with programs and data from another app.

Data redundancy: duplication of data in separate files – can lead to inconsistency.

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Database Approach

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Keys*Key: field or set of fields in a record that is

used to identify the recordPrimary key: field or set of fields that

uniquely identifies the recordForeign Key: A non-primary key attribute in

the table that is a primary key in the other table.

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Data ViewsPhysical View:Physical View: Where is data stored physically?

Drive, disk, surface, track, sector, RecordTape, block, record number (key)Used by programmers

Logical View:Logical View: What data is needed? How do users need the data to be arranged?Organize factors into tables for application useProvide a way for tables to cross-reference

*

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Accessing File StructuresSequential file structure e.g. payroll

Data is stored and accessed in a sequence according to a key field

Good for periodic processing of a large volume of data, but updating with new transactions can be troublesome

Direct file structure e.g. reservationsData stored randomly and accessed directly using

an index of keys and related storage addresses.Indexed Sequential file structure

Records stored sequentially on direct access medium (e.g. hdd) with address for each record.

Index keeps track of addresses for speed. Sequential access for large amounts of data

O’BRIEN 10

Record ProcessingOnline vrs Batch

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DBMS Components1.1. Data dictionaryData dictionary:: Stores definitions of data elements, and data Stores definitions of data elements, and data

characteristics e.g. data type, amount of storage: txt 30characteristics e.g. data type, amount of storage: txt 302.2. Data LanguagesData Languages::

Data definition language: Data definition language: Specifies content and structure of Specifies content and structure of database and defines each data element e.g keys, relationship database and defines each data element e.g keys, relationship

Data manipulation language: Data manipulation language: allows users to access and allows users to access and change data and produce reports. E.g. SQL, QBEchange data and produce reports. E.g. SQL, QBE

3.3. Application Development ToolsApplication Development Tools: : Programs to develop apps to Programs to develop apps to use the database, e.g. CASE toolsuse the database, e.g. CASE tools

4.4. Software Security: Software Security: protect database from hacking & protect database from hacking & unauthorised access.unauthorised access.

5.5. Archiving, backup & recovery systems: Archiving, backup & recovery systems: in case database is in case database is lost/crashes, it can be recovered from backups or archives.lost/crashes, it can be recovered from backups or archives.

6.6. Report WritersReport Writers: : tools to specify a report format for retrieving datatools to specify a report format for retrieving data

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Sample data dictionary report

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Structured Query Language (SQL)

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Examples of SQL Commands

Database Models1. Hierarchical2. Network3. Relational4. Multidimensional5. Object-oriented6. Object-relational

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Hierarchical Database ModelMay have more than one offspring, but only one parentTreelikeOne-to-many relationshipUsed for structured, routine types of transaction processing

Laudon 16

Network database modelMore complexMany-to-many relationshipMore flexible but doesn’t support ad hoc

requests well

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Relational Database ModelData elements stored in simple tablesCan link data elements from various tablesVery supportive of ad hoc requests but slower

at processing large amounts of data than hierarchical or network models

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The Relational Database Model

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The Relational Database Model (continued)

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The Relational Database Model (continued)

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Multidimensional DB modelA variation of

the relational model

Cubes of data and cubes within cubes

Popular for online analytical processing (OLAP) applications

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Object-oriented DB ModelData descriptions &

procedures that act on data are grouped together.

Key technology of multimedia web-based applications

Good for complex, high-volume applications

Can store more data types

Objects can be reused Faster data accessed

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Object-Relational DB ModelCombines features of object-oriented and

relational databasesStandard relational database with facilities

for new data types (e.g. video) and operations to be added.

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Types of Databases1. Operational DB – to support business

operations2. Analytical BD – Summarized data 4

analysis3. Data Warehouse*4. Distributed - data may be spread across

several smaller databases in different locations .

5. End-user –developed by managers and other users on their own PCs

6. External/on-line – pay for access to external statistical online databases

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Data Warehouses, Data Marts, and Data MiningData warehouse: Logical collection of data

gathered from many operational DBs to support business and decision making.

Data mart: subset of a data warehouseData mining: automated discovery of

patterns, trends and rules from data in data warehouse to predict business strategy.

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Data Warehouses, Data Marts, and Data Mining (continued)

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Figure 5.17: Elements of a Data Warehouse

Advantages of DBMSs

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Data sharingReduced data redundancy (no duplicates)Improved data consistency (more integrity)Data independence (data independent of the

application using it.)Improved data admin & control – better

overall protectionMore emphasis on data as a resource

Problems with DBMSs

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Concurrency problem – data used at same time - lock

Resource problems – costly initiallySecurity problems - cos data all in one place