Management Information Systems by Prof. Park Kyung-Hye Chapter 7 (8th Week) Databases and Data Warehouses 07

Objectives Databases and Data Warehouses Explain the difference between traditional file organization 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 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 2

Managing Digital Data Databases and Data Warehouses 3 Businesses collect and dissect data for many purposes Data can be stored in database format Databases have had a profound impact on business Easy access and manipulation An information industry has been created Database technology integrated with the Internet has contributed to commerce significantly

The Traditional File Approach Databases and Data Warehouses 4 Traditional file approach: no mechanism for tagging, retrieving, or manipulating data Database approach: provides powerful mechanism for managing and manipulating data Traditional approach is inconvenient: Program-data dependency Data redundancy: duplication of data High data redundancy Low data integrity Data integrity: accuracy of data

The Traditional File Approach (continued) Databases and Data Warehouses 5

The Database Approach Databases and Data Warehouses 6 Database approach: data organized as entities Entity: an object about which an organization chooses to collect data, such as: A single letter or a digit Character: smallest piece of data Field: single piece of information about entity People Events Products

The Database Approach (continued) Databases and Data Warehouses 7 Record: collection of related fields Build databases Database management system (DBMS): program used to: File: collection of related records Database fields can hold images, sounds, video clips, etc. Field name allows easy access to the data Populate a database with data Manipulate data in a database

The Database Approach (continued) Databases and Data Warehouses 8

The Database Approach (continued) Databases and Data Warehouses 9

The Database Approach (continued) Databases and Data Warehouses 10 Query : a message to the database requesting data from specific records and/or fields Not everyone should have access to all data Database must be properly secured Users will have different views of the database, based on the data they are allowed to see Sets user limits for access to data in the database Database administrator (DBA): the person responsible for managing the database DBMS is usually bundled with a programming language

The Database Approach (continued) Databases and Data Warehouses 11

The Database Approach (continued) Databases and Data Warehouses 12

Database Models Databases and Data Warehouses 13 Database model: general logical structure How records stored in the database How relationships between records are established Database models differ in: How records are linked to each other How users can navigate the database, retrieve records, and create records

The Relational Model Databases and Data Warehouses 14 Relational Model: consists of tables Based on relational algebra To design a relational database, you must understand the entities to be stored in the database and how they relate Tables are independent of each other, but can be related to each other Tuple : record (or row) Attribute : field (or column) Relation : table of records

The Relational Model (continued) Databases and Data Warehouses 15 Key: a field whose values identify records Primary key: a field by which records are uniquely identified Used to retrieve records Each record in the table must have a unique key value Composite key: combination of fields that serve as a primary key

The Relational Model (continued) Databases and Data Warehouses 16

The Relational Model (continued) Databases and Data Warehouses 17

The Relational Model (continued) Databases and Data Warehouses 18 Foreign key: a field that is common to two tables Join table: composite of tables Used to link the tables One-to-many relationship: one item in a table is linked to many items in the other table Two types of table relationships: This field is a primary key in one table and a foreign key in the other Many-to-many relationship: many items in a table are linked to many items of the other table

The Object-Oriented Model Databases and Data Warehouses 19 Object-oriented database model : uses object-oriented approach for the database structure Allows object to be “planted” in different data sets Encapsulation : combined storage of data and relevant procedures to process it Inheritance: the ability to create a new object by replicating the characteristics of an existing (parent) object Object-oriented databases (ODBs) store data objects, not records

The Object-Oriented Model (continued) Databases and Data Warehouses 20

Relational Operations Databases and Data Warehouses 21 Relational operation: creates a temporary subset of a table or tables Used to create a limited list or a joined table list Three important relational operations: Select a selection of records based on conditions Project a selection of certain columns from a table Join join data from multiple tables to create a temporary table

Structured Query Language Databases and Data Warehouses 22 Structured Query Language (SQL) : query language of choice for DBMSs Advantages of SQL: It is an international standard It is provided with most relational DBMSs It has easy-to-remember, intuitive commands

The Schema and Metadata Databases and Data Warehouses 23 Schema : a plan that describes the structure of the database, including: Data dictionary : a repository of information about the data and its organization Also called metadata: the data about the data Names and sizes of fields Identification of primary keys Relationships

The Schema and Metadata (continued) Databases and Data Warehouses 24 Metadata includes: Source of the data Tables related to the data Field and index information Programs and processes that use the data Population rules: what is inserted, or updated, and how often

The Schema and Metadata (continued) Databases and Data Warehouses 25

Data Modeling Databases and Data Warehouses 26 Databases must be carefully planned and designed to meet business goals Data modeling: analysis of an organization’s data and identification of the data relationships A proactive process Develops a conceptual blueprint of the database Entity relationship diagram: a graphical representation of all entity relationships

Data Modeling (continued) Databases and Data Warehouses 27 Entity relationship diagram is composed of: Boxes identify entities Lines indicate relationship between entities Cross-bars indicate mandatory fields Circles indicate optional Crow’s feet identify “many”

Data Modeling (continued) Databases and Data Warehouses 28

Data Modeling (continued) Databases and Data Warehouses 29

Databases on the Web Databases and Data Warehouses 30 Web is dependent on databases Java servlets Interface between Web and database required Interface may be programmed in one of several Web programming languages, including: Active server pages (ASP) PHP (Hypertext Preprocessor) Organizations must link their databases to the Web Web application program interfaces (APIs)

Databases on the Web (continued) Databases and Data Warehouses 31

Databases on the Web (continued) Databases and Data Warehouses 32

Data Warehousing Databases and Data Warehouses 33 Most data collections are used for transactions Typically relational Data warehouse: a large repository database that supports management decision making Data is collected from transactional databases Accumulation of transaction data is useful Data mart: a smaller collection of data focusing on a particular subject or department

From Database to Data Warehouse Databases and Data Warehouses 34 Transactional databases are not suitable for business analysis Contain only current, not historical data Data warehouse requires large storage capacity: Mainframe computers are often used Scalability is an issue Data warehouses grow continually

Phases in Data Warehousing Databases and Data Warehouses 35 Three phases in transferring data from a transactional database to a data warehouse: Extraction phase: create files from transactional database Transformation phase: cleanse and modify the data format Loading phase: transfer files to data warehouse A properly built data warehouse becomes a single source for all data required for analysis Data mining and online analytical processing (OLAP) use data in data warehouses

Phases in Data Warehousing (continued) Databases and Data Warehouses 36

Summary 37 Organizations collect vast amounts of data Database approach has several advantages over traditional file approach Character: smallest piece of data Field: made up of multiple characters Record: collection of related fields File: collection of related records Database management system (DBMS): tool to construct databases Relational and object-oriented database models have different advantages Keys are used to form links among entities Primary keys are unique identifiers Databases and Data Warehouses

Summary (continued) 38 Object-oriented database maintains objects that contain data and procedures that process it Structured Query Language (SQL) is an international standard for querying databases Database designer must construct a schema to construct a database Database designers conduct data modeling and create entity relationship diagrams to plan databases Many databases are linked to Web Data warehouses contain huge collections of historical transaction data Data warehouse requires data extraction, transformation, and loading of transactional data Invasion of privacy is exacerbated by database technology Databases and Data Warehouses