Management Information Systems By Effy Oz & Andy Jones Chapter 6: Databases and Data Warehouses www.cengage.co.uk/oz

Objectives Explain the difference between traditional file organisation and the database approach to managing digital data Explain how relational and object oriented database management systems are used to construct databases, populate them with data, and manipulate the data to produce information Enumerate the most important features and operations of a relational database, the most popular database model

Objectives (continued) Understand how data modeling and design creates a conceptual blueprint of a database Discuss how databases are used on the Web List the operations involved in transferring data from transactional databases to data warehouses

Managing Digital Data Businesses collect and dissect data Data can be stored in powerful database format Easy access and manipulation Databases have profound impact on business Database technology integrated with Internet

The Traditional File Approach Traditional file approach: no mechanism for manipulating data Database approach: has mechanism for manipulating data Traditional approach inconvenient High data redundancy Low data integrity Data redundancy: duplication of data Data integrity: accuracy of data

The Traditional File Approach (continued)

The Database Approach People Events Products Database approach: data organised as entities Entity: object that has data People Events Products Character: smallest piece of data Field: single piece of information about entity Record: collection of fields

The Database Approach (continued) File: collection of related records Database management system (DBMS): program used to build databases Populates with data Manipulates data Query: message requesting access to data

The Database Approach (continued) Database has security issues Database administrator (DBA): limits user access to database Requires users to enter codes DBMS bundled with fourth-generation languages

The Database Approach (continued)

The Database Approach (continued)

The Database Approach (continued)

Database Models Database model: general logical structure How records stored in database Records linked differently in different models Models constantly changing

The Relational Model Relational Model: consists of tables Based on relational algebra Tuple: record Attribute: field Relation: table Key: identifier field Used to retrieve records

Relational Model (continued)

The Relational Model (continued) Primary key: unique key Uniquely identifies record Required in table Composite key: combination of fields Serves as primary key Foreign key: shared field Links tables Join table: composite of tables

The Relational Model (continued)

The Relational Model (continued) Table relationships with other tables One-to-many relationship: one item in table linked to many items in other table Many-to-many relationship: many items in table linked to many items of other table

The Object-Oriented Model Object-Oriented model: uses object-oriented approach Encapsulation: combined storage of data and relevant procedures Allows object to be planted in different data sets Inheritance: creates new object by replicating characteristics of existing (parent) object

The Object-Oriented Model (continued)

Relational Operations Relational operation: create temporary subset of table Create limited list or joined table list Select records based on conditions Project columns Join tables to create temporary table

Structured Query Language Structured query language: language of choice for DBMSs Advantages Standardised language Used in many host languages Portable

The Schema and Metadata Schema: plan Describes structure of database Names and sizes of fields Identifies primary keys Data dictionary: repository of information about data

The Schema and Metadata (continued) Metadata: data about data Source of data Tables related to data Field information Usage of data Population rules

The Schema and Metadata (continued)

Data Modeling Databases must be carefully planned Data modeling: analysis and organisation of data Proactive process Develop conceptual blueprint Entity relationship diagram: graphical representation of relationships

Data Modeling (continued) Entity relationship diagram Boxes identify entities Lines indicate relationship Crossbars indicate mandatory fields Circles indicate optional Crows feet identify “many”

Data Modeling (continued)

Data Modeling (continued)

Databases on the Web Web dependent on databases Interface between Web and database required CGI ASP API

Databases on the Web (continued)

Data Warehousing Data collections used for transactions Accumulation of transaction data useful Data warehouse: large database Typically relational Supports decision making Data copied from transactional database Data mart: collection of data focusing on particular subject

From Database to Data Warehouse Transactional database not suitable for business analysis Only current data Not historic Data warehouse requires large storage capacity Mainframe computers used Scalability issue

Phases in Building a Data Warehouse Begin building data warehouse after equipment secured Extraction phase Create files from transactional database Transformation phase Cleanse and modify data Loading phase Transfer files to data warehouse

Phases in Building a Data Warehouse (continued)

Summary organisations collect vast amounts of data Database approach has advantages over traditional approach Character: smallest piece of data File: collection of records Designer must construct schema to construct database

Summary (continued) Database management system enables database construction and manipulation Relational and object-oriented database models have different advantages Keys used to form links among entities Object-oriented database maintains links differently SQL adopted as international standard

Summary (continued) Designers conduct data modeling to show required tables Databases often linked to Web Data warehouses contain huge collections of historical data Data warehouse allows data extraction, transformation, and loading Invasion of privacy is exacerbated by database technology