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2. DATABASES AND DATA WAREHOUSES
Chapter 3
DATABASES AND DATA WAREHOUSES
Building Business Intelligence

3. INTRODUCTION Businesses need business intelligence (BI)
Business intelligence – collective information e about your customers, competitors, business partners, environment, and internal operations
Enables effective, important and strategic decision making
Such Information need to be gathered and organized in data repositories such as databases, data warehouses and data marts then use IT tools (such as DBMS and data mining to define and analyze relationships within information.
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4. INTRODUCTION
IT tools help process information to create business intelligence according to…
OLTP (online transaction processing)
OLAP (online analytical processing)
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5. INTRODUCTION
OLTP – gathering and processing transaction information and updating existing information to reflect transaction
Databases and DBMS support OLTP
Operational database – database that supports OLTP
Simple queries which require information from single database
OLTP (on-line transaction processing)
– Major task of traditional relational DBMS
– Day-to-day operations: purchasing, inventory, banking, manufacturing,
payroll, registration, accounting, etc.
– Aims at reliable and efficient processing of a large number of transactions
and ensuring data consistency
• OLAP (on-line analytical processing)
– Major task of data warehouse system
– Data analysis and decision making
– Aims at efficient multidimensional processing of large data volumes
• Fast, interactive answers to large aggregate queries
• Distinct features (OLTP vs. OLAP):
– User and system orientation: customer vs. market
– Data contents: current, detailed vs. historical, consolidated
– Database design: ER + application vs. star + subject
– View: current, local vs. evolutionary, integrated
– Access patterns: update vs. read-only but complex queries
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6. INTRODUCTION
OLAP – manipulation of information to support decision making
Databases can help some
Data warehouses support only OLAP, not OLTP
Data warehouses – special forms of databases that support decision making
OLAP: Support more complex manipulation and in depth queries which require information from multiple DB
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7. INTRODUCTION McGraw-Hill
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8. RELATIONAL DATABASE MODEL
Database – logical collection of information you organize and access according to the logical structure of the information
Relational database – uses a series of two-dimensional tables or files to store information in the form of a database
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9. Databases Are… Collections of information
Created with logical structures
With logical ties within the information
With built-in integrity constraints
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10. Databases – Collections of Information
Databases have many tables
Solomon Enterprises as a concrete provider. Tables include:
Order
Customer
Concrete Type
Employee
Truck
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11. Databases – Collections of Information
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12. Databases – Created with Logical Structures
In databases, row numbers are irrelevant
In databases, columns have logical names (attributes) such as Order Date and Customer Name
Data dictionary – contains the logical structure of the information in a database
Data dictionary contains important information (or logical properties about your information) (characteristics of each field)
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13. Databases – Logical Ties within the Information
Logical ties (relationships) must exist between the tables to show how the tables related to each other.
Logical ties are created with primary and foreign keys
Primary key – field (or group of fields in some cases) that uniquely describe each record
Primary key: unique and cannot be blank
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14. Databases – Logical Ties within the Information
Foreign key – primary key of one file that appears in another file
Foreign keys help create relationships among tables, without them you have no way of creating logical ties among various files.
Table = file = relation (don’t confuse yourself)
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15. Databases – Logical Ties within the Information
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16. Databases – Built-in Integrity Constraints
Integrity constraint – rule that helps ensure the quality of information
Examples
Primary keys must be unique (can’t be blank “Null”)
Foreign keys cannot be blank (in general foreign keys can be “Null” but you can add a constraint that require to be entered (can’t be null)
Sales price cannot be negative
Phone numbers must have an area code
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17. DBMS TOOLS
Database management system (DBMS) – helps you specify the logical organization for a database and access and use the information within a database
Word processing software = document
Spreadsheet software = workbook
DBMS software = database
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18. DBMS TOOLS 5 software components DBMS engine Data definition subsystem
Data manipulation subsystem
Application generation subsystem
Data administration subsystem
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19. DBMS TOOLS McGraw-Hill
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20. DBMS Engine
DBMS engine – accepts logical requests from the various other DBMS subsystems, converts them into their physical equivalent, and actually accesses the database and data dictionary exist on a storage device.
DBMS engine separates the logical from the physical
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21. DBMS Engine
Physical view – how information is arranged, stored, and accessed on a storage device
Logical view – how you (knowledge worker) need to arrange and access information to meet your business needs.
Databases – you work only with logical views
There is one physical view but there maybe numerous knowledge workers who have different logical views of the information in a database
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22. Data Definition Subsystem
Data definition subsystem – helps you create and maintain the data dictionary and define the structure of the files in a database
Must create data dictionary for a database and define the structure of the table before entering any information
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23. Data Definition Subsystem
Add a new field in the data dictionary and delete a given field for all record in a file
Define logical structure (properties) of information in data dictionary
Field name: customer number, order date, ..
Field type: alphabetic, numeric, date, time
Form: is an area code required for phone number?
Default value: if no order date is entered the default is today’s date
Validation rule: can amount exceed 8?
Is an entry required?:must u enter delivery address for an order or it can be blank?
Can there be duplicates?: primary keys can’t be duplicated, but what about amounts?

24. Data Manipulation Subsystem
Data manipulation subsystem – helps you add, change, and delete information
Primary interface between you and a database
Views
Report generators
QBE tools
SQL
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25. Views View – allows you to see the contents of a database file
Similar to a spreadsheet view
Make changes, add and remove records.
Sort
Query
Find
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26. Views Sort Find Add a new record McGraw-Hill
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27. Report Generators
Report generator – helps you quickly define formats of reports and what information you want to see in a report
Save report formats to use later
Uses a wizard interface
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28. Report Generators Specify the fields you want in a report
Specify the layout of the report
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29. Report Generators McGraw-Hill
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30. QBE Tools
Query-by-example (QBE) tool – helps you graphically design the answer to a question
“What driver most often delivers concrete to Triple A Homes?”
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31. QBE Tools
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32. SQL
Structured query language (SQL) – standardized fourth-generation language found in most DBMSs
Performs same task as QBE
Uses sentence structure instead
Mostly used by IT people
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33. Application Generation Subsystem
Application generation subsystem – contains facilities to help you develop transaction-intensive applications
Data entry screens (called forms in Access)
Programming languages
Interfaces
Mostly used by IT people
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34. Data Administration Subsystem
Data administration subsystem – helps you manage the overall database environment
Backup and recovery
Security management(CRUD)
Query optimization
Concurrency control
Change management
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35. Data Administration Subsystem
Backup and recovery
Periodically back up information
Recover a database after a failure
Backup: a copy of information stored on a computer.
Recovery: the process of reinstalling the backup information in the event information was lost.
Security management
Who has access to what information
What type of access those people have (Who can perform CRUD tasks on information) (CRUD: Create, Read, Update and Delete)
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36. Data Administration Subsystem
Query optimization
Take queries from users and restructure them to minimize response time. (find shortest route to information)
Reorganization facilities:
how DBMS engine physically access information and reorganize how information is physically stored
Concurrency control
The validity of database updates when multiple users attempt to access and change the same information What happens if two people simultaneously try to change the same information?
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37. Data Administration Subsystem
Change management
What is the effect of structural changes to a database?
What if you add a new column?
What happens if you delete a column?
What happens if you change a column’s attributes?
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38. DATA WAREHOUSES & DATA MINING
Data warehouses support OLAP and decision making
Data warehouses do not support OLTP
Data-mining tools are tools for working with data warehouse information
DBMS software = database
Data-mining tools = data warehouse
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39. What Is a Data Warehouse?
Data warehouse – logical collection of information – gathered from operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks
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40. What Is a Data Warehouse?
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41. What Is a Data Warehouse?
Multidimensional
Rows and columns
Also layers
Many times called hypercubes
What are the dimensions in Figure 3.8 on page 140?
Data warehouse contains summarized information it doesn’t contains details about each interaction.
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42. What Are Data-Mining Tools?
Data-mining tools – software tools that you use to query information in a data warehouse
Query-and-reporting tools
Intelligent agents
Multidimensional analysis tools
Statistical tools
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43. What Are Data-Mining Tools?
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44. Query-and-Reporting Tools
Query-and-reporting tools – similar to QBE tools, SQL, and report generators in the typical database environment
Also similar to pivot tables in Excel
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45. Intelligent Agents
Use various Artificial Intelligence (AI) tools such as neural networks and fuzzy logic to form the basis for “information discovery” and building BI
Help you find hidden patterns in information
Chapter 4 focuses on these
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46. Multidimensional Analysis Tools
Multidimensional analysis (MDA) tools – slice-and-dice techniques that allow you to view multidimensional information from different perspectives
Bring new layers to the front
Reorganize rows and columns
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47. Statistical Tools
Help you apply various mathematical models to the information stored in a data warehouse to discover new information
Regression analysis
Analysis of variance
And so on
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48. Data Marts Data warehouses are organizationwide
Data marts have subsets of an organizationwide data warehouse
Data mart – subset of a data warehouse in which only a focused portion of the data warehouse information is kept. It is smaller more manageable data for particular needs.
Data marts use the same data mining tools like data warehousing (Query-and-reporting tools, Intelligent agents, Multidimensional analysis tools and Statistical tools)
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49. Data Marts McGraw-Hill
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50. Data Mining as a Career Opportunity
Knowledge of data mining can be a substantial career opportunity for you
Business Objects
SAS
Cognos
Informatica
Many others
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51. Considerations in Using a Data Warehouse
Do you need a data warehouse?
DBMS may offer all you need and data warehouse are expensive and require extensive and most often expensive support.
Do all employees need the entire data warehouse?
Consider a data mart
How up-to-date must information be?
“Snapshot” concept to compare database information with data warehouse
What data-mining tools do you need?
Training can be expensive
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52. BI Revisited
BI: improve timeline and quality of input for decision making by helping knowledge worker understands:
Capabilities available in organization
State of arts, trends and future direction of market
Technological, demographic, economic, social and regulatory environment in which organization compete
Action of competitors and implications of these actions
BI : INTERNAL INFORMATION
EXTERNAL INFORMATION
Competitive Intelligence: business intelligence focused on external competitive environment

53. BUSINESS INTELLIGENCE
BI : INTERNAL INFORMATION
EXTERNAL INFORMATION
Competitive Intelligence: business intelligence focused on external competitive environment

54. Strategic and Competitive Opportunities with BI
Corporate performance management
Optimizing customer relations
Traditional decision support
Management reporting of BI
Information right time, location, and form (personal information dimensions)

55. IT Support for Business Intelligence
Web supports many BI systems
Movement toward specialized BI packages
Digital dashboard – displays key information gathered from several sources on computer screen in format tailored to an individual needs and wants

56. IT Support for Business Intelligence

57. INFORMATION OWNERSHIP
Strategic management support
The sharing of information with responsibility
Information cleanliness
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58. Strategic Management Support
Chief privacy officer (CPO) – ensuring that information is used in an ethical way
Chief security officer (CSO) – ensuring security of information (e.g., firewalls)
Chief information officer (CIO) – oversees every aspect of an organization’s information resource
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59. Strategic Management Support
Data administration – plans for, oversees the development of, and monitors the information resource.
Assure all information requirement can be and are being met.
Database administration – responsible for the more technical aspects and operational aspects of managing information
Defining and organizing database structures and contents, developing security procedures, monitor developing DB.
Both often report to the CIO
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60. The Sharing of Information with Responsibility
Someone has to accept full responsibility for providing a specific peace of information and ensuring the quality of that information.
If you create it, you “own” it
You will also share it with others
Because you “own” it, you are responsible for its quality
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61. Information Cleanliness
Database and data warehouse information must be “clean”
No errors
No duplicates
DBMS can find utilities to help clean your information
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62. Designing and building relational database
Four steps to go about designing a database
Define entity classes and primary keys
Define relationships among entity classes
Define information fields for each relation and Define cardinality for each relation
Use data definition language to create your DB
Before you design a database you need to capture business rules which help you define the correct structure of your DB.
Business Rules: are statements concerning the information you need to work with and the relationships within the information

63. Extended learning module
E-R diagram: entity relation diagram
Entity class: concept (people, places or things) about which you wish to store information and that you can identify with a unique key.
Instance: an occurrence of an entity class that can be uniquely described with a primary key.
Intersection relation (composite relation): a relation you create to eliminate many to many relationship. It called so because it represent an intersection of the primary keys between the first two relations
Composite primary key: consist of the primary key field from the two intersection relations
Cardinality: numerical nature of a relationship (1:1, 1:M, M:1, M:M)

64. Normalization
Normalization : a process of assuring that a relational database structure can be implemented as a series of two- dimensional relations
Eliminate repeating groups or M:M relationships
Assure that each field in a relation depends only on the primary key for that relation
Removed all derived field from the relation