صفحه 1:
Chapter 7
Enterprise Databases, Data
Warehouses, and Business
Intelligence
صفحه 2:
Objectives
O Advantages of shared databases.
O Compare relational vs. object oriented
databases.
O Describe the differences between schemas,
views, and indexes.
O Shared vs. distributed databases.
O Data warehouses and Business Intelligence.
صفحه 3:
Enterprise Data - Scaling Up
QO Database: A collection of data and information
describing items of interest to an organization.
O Enterprise Database: A collection of data
designed to be shared by many users within an
organization.
صفحه 4:
Both Actual Data and Schema are
Shared
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صفحه 5:
Database Mangement
O The Functions of Database Management:
۲ Integrating Databases
Reducing Redundancy
Sharing Information
Maintaining Integrity
Enabling Database Evolution
صفحه 6:
DBMS in Systems
Figure 7.2 Relationship of DBMS to Other Programs in Computer Memory
Application
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صفحه 7:
Enterprise Data Model
O Enterprise Data Model/Entity Relationship: A
graphical representation of the items (the
entities) of interest about which data is
captured and stored in the database.
صفحه 8:
Schema
O Schema: The structure of a database.
O Schema for Relational Database
® Relational Database: A database in which
the data are structured in a table format
consisting of rows and columns.
صفحه 9:
Relational Schema
Status
Balance
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Figure 7.4 Schema for Customer-Order Relationship
Customer relation
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DATABASE SCHEMA
صفحه 10:
Object Orientation
O Schema for Object-Oriented Database
™ Object-oriented Database: A database that
stores data and information about objects.
™ Object: A component that contains data
about itself and how it is to be processed.
® Action/Method: An instruction that tells a
database how to process an object to
produce specific information.
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صفحه 11:
Object Oriented Schema
Figure 7.5
Classes in an Object-Oriented Database Featuring Customer and Order Objects,
Object class
Attributes
| Actions (Methods)
11
صفحه 12:
User views
O View: A subset of one or more databases,
created either by extracting copies of records
from a database or by merging copies of
records from multiple databases.
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صفحه 13:
Enterprise Database Structures
Views (Continued)
13
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صفحه 14:
Indexing
۲ 9 A data file that contains identifying
information about each record and its location
in storage.
O Record Key: In a database, a designated field
used to distinguish one record from another.
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صفحه 15:
Enterprise Database Structures
Indexes (Continued)
Figure 7.8 Using an index w Rewieve Data
Search index for 1D.
record key.
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15
صفحه 16:
Integration
O Web-based Integration: Makes data from
enterprise databases available to users
connecting through the Internet (including
enterprise intranets and extranets).
16
صفحه 17:
Databases and the Internet
Figure 7.14 Web-F
صفحه 18:
Distributed Databases
O Shared Database: A database shared among
many users and applications.
O Distributed Database: A database that resides
in more than one system in a distributed
network. Each component of the database can
be retrieved from any node in the network.
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صفحه 19:
19
Partitioning and Replication
QO Partitioning: A method of database distribution in
which different portions of the database reside at
different nodes in the network.
™ Vertical
™ Horizontal
O Replication: A method of database distribution in
which one database contains data that are
included in another database.
™ Real time
™ Cascade
™ Batch
صفحه 20:
Distribution Strategies
O Geographic Distribution Strategy: A database
distribution strategy in which the database is
located in a region where the data and
information are used most frequently.
O Functional Distribution Strategy: A database
distribution strategy in which the database is
distributed according to business functions.
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صفحه 21:
Designing a Distributed 6
O Database Directory: The component of a shared
database that keeps track of data and information.
O Other Design Factors
Storage Costs
Processing Costs
Communication Costs
Retrieval and Processing
Reliability
Frequency of Updates and Queries
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صفحه 22:
Data Warehouses and OLAP
O Data Warehouse: A large data store, designed
from inquiries, that combines details of both
current and historical operations, usually drawn
from a number of sources.
O Online Analytical Processing (OLAP): Database
processing that selectively extracts data from
different points of view.
22
صفحه 23:
Comparison of Enterprise Databases
and Data Warehouses
Table 7.1 Comparison of Enterprise Databases and Data Warehouses
ENTERPRISE DATABASE DATA WAREHOUSE
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صفحه 24:
Data Warehouse
Figure 7.17 Data Warehouses and Data Marts Support Analysis and Decision Making
Enterprise
databases
صفحه 25:
Data Warehouses and OLAP
Definition
O Data Mining: Uses software designed to detect
information hidden in the data.
O Data Marts: Processed to focus on a specific
area of activities or isolated scientific or
commercial processes.
25
صفحه 26:
Business Intelligence
Supporting Managerial Decision
Making
صفحه 27:
Issues
O MIs: Reporting
O Data-Driven DSS: Business Intelligence
O Model- -Driven DSS: Models and Modeling
OGDSS and ESS
O Case Study: MasterCard
صفحه 28:
Decision Levels and
Application Systems
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صفحه 29:
MIS vs. DSS (Data Driven and Model
Driven)
Onis:
™ Provides reports based on routine flow
of data.
™@ Assists in general control of the organization.
™@ Exception reports used to reduce volume and
focus on items that require management
attention.
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صفحه 30:
MIS Reports
O Paper or online
O Can includes text, graphs, or both.
O Batch vs. Real-time
O Fixed vs. Ad Hoc (a continuum)
O Summary vs. Detail
O Types include:
@ Exception
@Trend
® Validation (such as Trial Balance)
30
صفحه 31:
Data-Driven DSS
(a.k.a. Business Intelligence)
O Also known as. Query/inquiry, Data Mining, and OLAP
(Online Analytical Processing).
O Goal is to determine where we are or where we've been.
O “Business Intelligence” has emerged as common term.
O Sometimes also called Datamining, though this generally
implies using statistical techniques such as correlation
analysis and clustering to find patterns and relationships
in large databases.
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صفحه 32:
Goals of BI
O Enables users to identify and understand the
key trends and events driving their businesses.
O Allows employees to sift through and analyze
large amounts of data that the company makes
available for them.
O Helps business managers at all levels make
better decisions quicker.
32
صفحه 33:
What is BI Used For?
OTo perform trend analyses on product, sales,
event (i.e. promotions and advertising
campaigns) and financial information.
™ Sales per office or region and then drill down to lower
level details to uncover what is driving the trends.
Olt is also used for exception-reporting and for
budgeting, planning, and forecasting.
33
صفحه 34:
BI Tool Capabilities
O Support large volumes of data and an unlimited
number of dimensions
O Can aggregate data
™ Sums, averages, maximums, minimums, percentage of
total, and user-defined functions or rules.
O Can contain analytical engines that perform
computations.
™ Rankings, ratios, or variances (i.e., This-year-to-last-
year or actual-versus-budget comparisons), Revenue
or expense allocations, Currency conversions, etc.
34
صفحه 35:
Most BI Tools also include
graphics capabilities
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صفحه 36:
Data Sources for BI Include
O Relational Data Bases (including Data
Warehouses)
O Data Marts
™Star Schemas
™ Facts and Dimensions
O Cubes (Facts and Dimensions)
36
صفحه 37:
Data Warehouse
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صفحه 38:
Data Warehouses Contain Data from
Many Sources (a.k.a. Domains)
Figure 11.4 88 for custo
صفحه 39:
Cube Example:
Sales Information
Sales information can be represented in the cube
below. You will be able to derive many measures
based on the dimensions below
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39
صفحه 40:
Some Leading BI Vendors
O Enterprise Query/Reporting (RDBMS Based):
® Actuate
™ Crystal Reports
™ Information Builders / WebFocus
O OLAP (Data Mart and Cube Based):
™@ MicroStrategy
® Hyperion
® Oracle
™ Business Objects (also includes reporting tools)
™ Cognos (also includes reporting tools)
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صفحه 41:
Demo Sites
O Cognos PowerPlay:
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® http://www.cognosdemo.com/temple/
O Information Builders Web FOCUS:
® www. informationbuilders.com/test_drive/inde
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® www.nyc.gov/html/doh/html/rii/index.html|
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صفحه 42:
For more information...
42
O Bill Inmon:
® http://www. billinmon.com/
O Ralph Kimball:
® http://www. rkimball.com/
O Data Management Review:
® http://www.dmreview.com/
Data Warehouse:
@ http://www.datawarehouse.com
صفحه 43:
DSS: Decision Support System
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صفحه 44:
سم
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صفحه 45:
Prediction
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صفحه 46:
Marketing Sales Forecast
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صفحه 47:
Time Series Components
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صفحه 48:
Forecasting Uses
O Marketing O HRM
™ Future sales ™ Labor costs
® Consumer ® Absenteeism
preferences/trends @ Turnover
@ Sales strategies O Strategy
O Finance ® Rivals’ actions
™ Interest rates ™ Technological change
™ Cash flows ™ Market conditions
® Financial market
conditions
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صفحه 49:
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صفحه 50:
Group Decision Support Systems
(GDSS)
O Interactive computer-based system.
O Facilitates solution to unstructured problems.
O Set of decision makers working together as a
group.
50
صفحه 51:
EIS: Enterprise Information System
(aka Executive Information System and Executive Support System)
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صفحه 52:
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