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Data base and data warehouse
1.
1 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning DATABASE SYSTEMS, DATA WAREHOUSES, AND DATA MARTS CHAPTER 3 Hossein BIDGOLI MIS
2.
2 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning LO1 Define a database and a database management system. LO2 Explain logical database design and the relational database model. LO3 Define the components of a database management system. LO4 Summarize recent trends in database design and use. LO5 Explain the components and functions of a data warehouse. l e a r n i n g o u t c o m e s Chapter 3 Database Systems, Data Warehouses, and Data Marts
3.
3 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning LO6 Describe the functions of a data mart. l e a r n i n g o u t c o m e s (cont’d.) Chapter 3 Database Systems, Data Warehouses, and Data Marts
4.
4 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Databases • Database – Collection of related data that can be stored in a central location or in multiple locations – Usually a group of files • File – Group of related records – All files are integrated • Record – Group of related fields • Data hierarchy
5.
5 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Exhibit 3.1 Data Hierarchy
6.
6 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Databases (cont’d.) • Critical component of information systems – Any type of analysis that’s done is based on data available in the database • Database management system (DBMS) – Creating, storing, maintaining, and accessing database files • Advantages over a flat file system
7.
7 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Exhibit 3.2 Interaction between the User, DBMC, and Database
8.
8 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Types of Data in a Database • Internal data – Collected within organization • External data – Sources
9.
9 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts BI in Action: Law Enforcement • Business intelligence (BI) – Used in law enforcement as well as in the business world • Richmond, Virginia – System generates BI reports that help pinpoint crime patterns – Allocate manpower to days and locations where crime likely to occur
10.
10 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Methods for Accessing Files • Sequential file structure – Records organized and processed in numerical or sequential order – Organized based on a “primary key” – Usually used for backup and archive files • Because they need updating only rarely • Random access file structure – Records can be accessed in any order – Fast and very effective when a small number of records need to be processed daily or weekly
11.
11 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Methods for Accessing Files (cont’d.) • Indexed sequential access method (ISAM) – Records accessed sequentially or randomly – Depending on the number being accessed • Indexed access – Uses an index structure with two parts: • Indexed value • Pointer to the disk location of the record matching the indexed value
12.
12 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Logical Database Design • Physical view – How data is stored on and retrieved from storage media • Logical view – How information appears to users – How it can be organized and retrieved – Can be more than one logical view
13.
13 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Logical Database Design (cont’d.) • Data model – Determines how data is created, represented, organized – Includes: • Data structure • Operations • Integrity rules • Hierarchical model – Relationships between records form a treelike structure
14.
14 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Exhibit 3.3 A Hierarchical Model
15.
15 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Logical Database Design (cont’d.) • Network model – Similar to the hierarchical model – Records are organized differently
16.
16 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Exhibit 3.4 A Network Model
17.
17 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts The Relational Model • Relational model – Uses a two-dimensional table of rows and columns of data • Data dictionary – Field name – Field data type – Default value – Validation rule
18.
18 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts The Relational Model (cont’d.) • Primary key – Unique identifier • Foreign key – Establishes relationships between tables • Normalization – Improves database efficiency – Eliminates redundant data – 1NF through 3NF (or 5NF)
19.
19 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts The Relational Model (cont’d.) • Data retrieval – Select – Project – Join – Intersection – Union – Difference
20.
20 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Components of a DBMS • Database engine • Data definition • Data manipulation • Application generation • Data administration
21.
21 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Database Engine • Heart of DBMS software • Responsible for data storage, manipulation, and retrieval • Converts logical requests from users into their physical equivalents
22.
22 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Data Definition • Create and maintain the data dictionary • Define the structure of files in a database – Adding fields – Deleting fields – Changing field size – Changing data type
23.
23 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Data Manipulation • Add, delete, modify, and retrieve records from a database • Query language – Structured Query Language (SQL) • Standard fourth-generation query language used by many DBMS packages • SELECT statement – Query by example (QBE) • Construct statement of query forms • Graphical interface
24.
24 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Application Generation • Design elements of an application using a database – Data entry screens – Interactive menus – Interfaces with other programming languages
25.
25 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Data Administration • Used for: – Backup and recovery – Security – Change management • Create, read, update, and delete (CRUD) • Database administrator (DBA) – Individual or department – Responsibilities
26.
26 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Recent Trends in Database Design and Use • Data-driven Web sites • Natural language processing • Distributed databases • Client/server databases • Object-oriented databases
27.
27 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Data-Driven Web Sites • Data-driven Web site – Interface to a database – Retrieves data and allows users to enter data • Improves access to information • Useful for: – E-commerce sites that need frequent updates – News sites that need regular updating of content – Forums and discussion groups – Subscription services, such as newsletters
28.
28 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Distributed Databases • Distributed database – Data is stored on multiple servers placed throughout an organization • Reasons for choosing • Approaches for setup – Fragmentation – Replication – Allocation • Security issues
29.
29 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Client/Server Databases • Client/server database – Users’ workstations (clients) linked in a local area network (LAN) to share the services of a single server – Server processes data – Returns only records meeting request
30.
30 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Object-Oriented Databases • Object-oriented database – Object consists of attributes and methods • Encapsulation – Grouping objects along with their attributes and methods into a class • Inheritance – New objects can be created faster and more easily by entering new data in attributes • Interaction with an object-oriented database takes places via methods
31.
31 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Data Warehouses • Data warehouse – Collection of data used to support decision-making applications and generate business intelligence • Multidimensional data • Characteristics – Subject oriented – Integrated – Time variant – Type of data – Purpose
32.
32 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Input • Variety of sources – External – Databases – Transaction files – ERP systems – CRM systems
33.
33 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts ETL • Extraction, transformation, and loading (ETL) • Extraction – Collecting data from a variety of sources – Converting data into a format that can be used in transformation processing • Transformation processing – Make sure data meets the data warehouse’s needs • Loading – Process of transferring data to the data warehouse
34.
34 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Exhibit 3.9 A Data Warehouse Configuration
35.
35 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Storage • Raw data • Summary data • Metadata
36.
36 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Output • Data warehouse supports different types of analysis – Generates reports for decision making • Online analytical processing (OLAP) – Generates business intelligence – Uses multiple sources of information and provides multidimensional analysis – Hypercube – Drill down and drill up
37.
37 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Exhibit 3.10 Slicing and Dicing Data
38.
38 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Output (cont’d.) • Data-mining analysis – Discover patterns and relationships • Reports – Cross-reference segments of an organization’s operations for comparison purposes – Find patterns and trends that can’t be found with databases – Analyze large amounts of historical data quickly
39.
39 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Data Warehouse Applications at InterContinental Hotels Group (IHG) • The new system has increased the company’s query response time from hours to minutes • It has generated valuable BI on both its customers and the competition • Future plans include the migration of financial data, which will enable IHG to perform side-by- side analyses of operations, marketing, sales, and financial data
40.
40 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Data Marts • Data mart – Smaller version of data warehouse – Used by single department or function • Advantages over data warehouses • More limited scope than data warehouses
41.
41 MIS, Chapter 3 ©2011
Course Technology, a part of Cengage Learning Chapter 3 Database Systems, Data Warehouses, and Data Marts Summary • Databases – Accessing files – Design principles – Components – Recent trends • Data warehouses and data marts
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