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TIM 50 - Business Information Systems
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Lecture 15
Business Paper Initial
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Instructor: Ram Akella
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UC Santa Cruz
November 12, 2015
Database Assignment 2
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Due Thursday, 11/19
Zheijang Reading
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Today (+Cisco+Alibaba)
Essentials of Management Information Systems
Application Lifecycle Model
concluding remarks
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Now due Mon, 11/16, 11.59 pm
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
The D atabase A pproach t o D ata Management
ALM rarely followed precisely
• Database: • Collection of related files containing records on people, places, or things.
• Prior to dig. DBs, business used paper files.
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Many times projects loop between stages
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ALM followed more closely in larger companies
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Alternative:
• Entity:
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• Generalized category representing person, place, thing on which we store info.
• E.g., SUPPLIER, PART
• Attributes:
Rapid Iterative Prototyping
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• Specific characteristics of each entity:
• SUPPLIER name, address
(Cisco did some of this in the ERP case.)
• PART description, unit price, supplier
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Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
The D atabase A pproach t o D ata Management
The D atabase A pproach t o D ata Management
• Relational database:
A Relational Database Table
• Organize data into tables • One table for each entity:
• E.g., (CUSTOMER, SUPPLIER, PART, SALES)
• Fields (columns) store data representing an attribute. • Rows store data for separate records. • Key field: uniquely identifies each record. • Primary key: • One field in each table
• Cannot be duplicated
A relational database organizes data in t he f orm of t wo-­dimensional t ables. Illustrated here is a t able f or t he e ntity SUPPLIER s howing how it represents t he entity a nd its a ttributes. Supplier_Number is t he k ey f ield.
• Provides unique identifier for all information in any row
Figure 5-­1
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Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
The D atabase A pproach t o D ata Management
The D atabase A pproach t o D ata Management
The PART Table
• Establishing relationships
• Entity-­relationship diagram
• Used to clarify table relationships in a relational database
• Relational database tables may have:
• One-­to-­one relationship
• One-­to-­many relationship
• Many-­to-­many relationship
• Requires creating a table (join table, Intersection relation) that links the two tables to join information
Figure 5-­2
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
The D atabase A pproach t o D ata Management
The D atabase A pproach t o D ata Management
• Normalization
A Simple Entity-­Relationship Diagram
• Process of streamlining complex groups of data to:
• Minimize redundant data elements.
• Minimize awkward many-­to-­many relationships.
• Increase stability and flexibility.
• Referential integrity rules
• Used by relational databases to ensure that relationships between coupled tables remain consistent.
This diagram shows t he relationship between t he e ntities SUPPLIER and PART.
Figure 5-­3
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
The D atabase A pproach t o D ata Management
The D atabase A pproach t o D ata Management
Sample Order Report
The Final Database Design with Sample Records
Figure 5-­5
Figure 5-­4
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Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
The D atabase A pproach t o D ata Management
Database Management Systems
Entity-­Relationship Diagram for the Database
with Four Tables
DBMS
• Specific type of software for creating, storing, organizing, and accessing data from a database
• Separates the logical and physical views of the data
• Logical view: how end users view data
• Physical view: how data are actually structured and organized
This diagram shows the relationship between the entities SUPPLIER, A RT, LINE_ITEM, and ORDER .
• Examples of DBMS: Microsoft Access, DB2, Oracle Database, Microsoft SQL Server, MySQL
Figure 5-­6
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Database Management Systems
Database Management Systems
Human Resources Database with Multiple Views
Operations of a Relational DBMS
• Select: Figure 5-­7
• Creates a subset of all records meeting stated criteria
• Join: • Combines relational tables to present the server with more information than is available from individual tables
• Project: • Creates a subset consisting of columns in a table
• Permits user to create new tables containing only desired information
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Database Management Systems
Database Management Systems
The Three Basic Operations of a Relational DBMS
Capabilities of Database Management Systems
• Data definition capabilities:
• Specify structure of content of database.
• Data dictionary:
• Automated or manual file storing definitions of data elements and their characteristics.
Figure 5-­8
• Querying and reporting:
• Data manipulation language
• Structured query language (SQL)
• Microsoft Access query-­building tools
The select, project, and join operations enable data f rom two different tables to be combined and only selected attributes to be displayed.
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Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Database Management Systems
Database Management Systems
Example of an SQL Query
An Access Query
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Illustrated here are the SQL statements for a query to s elect suppliers for parts 137 or 150. They produce a list with the same results as Figure 5-­8.
Figure 5-­11
Figure 5-­10
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© Copyr ight © 2011 Pear son Education, Inc. publishing Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Database Management Systems
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Object-­Oriented DBMS (OODBMS)
Data Warehouses
• Data warehouse:
• Stores data and procedures that act on those data as objects to be retrieved and shared
• Database that stores current and historical data for decision makers
• Better suited for storing graphic objects, drawings, video, than DBMS designed for structuring data only
• Consolidates and standardizes data from many systems, • Data can be accessed but not altered
• Used to manage multimedia components or Java applets in Web applications
• Data mart:
• Subset of data warehouses that is highly focused and isolated for a specific population of users
• Relatively slow compared to relational DBMS
• Object-­relational DBMS: provide capabilities of both types
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Components of a Data Warehouse
Business Intelligence, Multidimensio nal Mining
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Data A nalysis, and Data Business intelligence: tools for consolidating, analyzing, and providing access to data to improve decision making
• Software for database reporting and querying
• Tools for multidimensional data analysis (online analytical processing -­-­OLAP)
• Data mining
Figure 5-­12
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
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Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Business Intelligence
Online Analytical Processing (OLAP)
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Supports multidimensiona l data analysis
• Enable users to view same data in different ways using multiple dimensions
• Dimension can be — product, pricing, cost, region, or time period
• E.g., comparing sales in East in June versus May and July
Figure 5-­13
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© Copyr ight © 2011 Pear son Education, Inc. publishing as Pr entice Hall
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Multidimensiona l Data Model
Data Mining
• Finds hidden patterns and relationships in large databases • Types of information obtainable from data mining
• Associations: occurrences linked to single event
• Sequences: events linked over time
• Classifications: patterns describing a group an item belongs to
• Clusters: discovering as yet unclassified groupings
• Forecasting: uses series of values to forecast future values
Figure 5-­14
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© Copyr ight © 2011 Pear son Education, Inc. publishing Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Chapter 5 Foundations of B usiness Intelligence: D atabases a nd Information Management
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Using D atabases t o Improve B usiness Performance a nd D ecision Making
Data Mining
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Text Mining
• One popular use of data mining: identifying profitable customers
• Unstructured data (mostly text files) accounts for 80 percent of an organization’s useful information.
• Predictive analysis: • Text mining -­-­ extract k ey elements from, discover patterns in, and summarize large unstructured data sets.
• Uses historical data, and assumptions about future conditions to predict outcomes of events
•
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Web Mining
• Discovery and analysis of useful patterns and information from the Web
• E.g. such the probability a customer will respond to an offer or purchase a specific product
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Zhejiang Discussion
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What could China Telecom (and Zhejiang
Telecom) in particular do to lure customers
from China Mobile?
How could any of these strategies make
use of the data in Zhejiang Telecom’s data
warehouse?
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