1. Databases and Data Warehouses
Chapter 3
Databases and Data Warehouses

2. STUDENT LEARNING OUTCOMES
Describe business intelligence and its role in an organization.
Differentiate between databases and data warehouses with respect to their focus on OLTP and OLAP.
List and describe the key characteristics of a relational database.

3. STUDENT LEARNING OUTCOMES
Define the five software components of a database management system.
List and describe the key characteristics of a data warehouse.
Define the four major types of data-mining tools in a data warehouse environment.
List key considerations in information ownership in an organization.

4. Can Companies Keep Your Personal Information Secure and Private?
Databases and data warehouses are organizational repositories of information
Much of the information is personal
It must be secure
If hackers get your personal information, you can suffer from identity theft

5. Can Companies Keep Your Personal Information Secure and Private?
Top-10 incidents of personal information loss by organizations
Could affect over 53 million people
CardSystems lost information on 40 million customers
Many others

6. Can Companies Keep Your Personal Information Secure and Private?
Have you been a victim of identity theft?
What happened?
What did you do to recover?
How long did it take?

7. INTRODUCTION Businesses need business intelligence (BI)
Business intelligence – knowledge about your customers, competitors, business partners, environment, and internal operations
Enables effective decision making
Information on steroids

8. INTRODUCTION
IT tools help process information to create business intelligence according to…
OLTP (online transaction processing)
OLAP (online analytical processing)

9. INTRODUCTION
OLTP – gathering and processing transaction information and updating existing information to reflect transaction
Databases support OLTP
Operational database – database that supports OLTP

10. 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

11. INTRODUCTION

12. INTRODUCTION This chapter – database and data warehouse concepts
Along with some privacy and security considerations

13. 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

14. Databases Are… Collections of information
Created with logical structures
With logical ties within the information
With built-in integrity constraints

15. Databases – Collections of Information
Databases have many tables
Solomon Enterprises as a concrete provider. Tables include:
Order
Customer
Concrete Type
Employee
Truck

16. Databases – Collections of Information

17. Databases – Created with Logical Structures
In databases, row numbers are irrelevant
In databases, columns have logical names such as Order Date and Customer Name
Data dictionary – contains the logical structure of the information in a database

18. Databases – Logical Ties within the Information
Logical ties must exist between the tables
Logical ties are created with primary and foreign keys
Primary key – field (or group of fields in some cases) that uniquely describe each record

19. 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
Table = file = relation (don’t confuse yourself)

20. Databases – Logical Ties within the Information

21. Databases – Built-in Integrity Constraints
Integrity constraint – rule that helps ensure the quality of information
Examples
Primary keys must be unique
Foreign keys cannot be blank
Sales price cannot be negative
Phone numbers must have an area code

22. 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

23. DBMS TOOLS 5 software components DBMS engine Data definition subsystem
Data manipulation subsystem
Application generation subsystem
Data administration subsystem

24. DBMS TOOLS

25. DBMS Engine
DBMS engine – accepts logical requests, converts them into their physical equivalent, and accesses the database and data dictionary
DBMS engine separates the logical from the physical

26. 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
Databases – you work only with logical views

27. 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 before entering any information

28. 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

29. Views View – allows you to see the contents of a database file
Similar to a spreadsheet view
Make changes
Sort
Query

30. Views

31. 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

32. Report Generators Specify the fields you want in a report
Specify the layout of the report

33. Report Generators

34. 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?”

35. QBE Tools

36. 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

37. Application Generation Subsystem
Application generation subsystem – contains facilities to help you develop transaction-intensive applications
Data entry screens (called forms in Access)
Programming languages
Mostly used by IT people

38. Data Administration Subsystem
Data administration subsystem – helps you manage the overall database environment
Backup and recovery
Security management
Query optimization
Concurrency control
Change management

39. Data Administration Subsystem
Backup and recovery
Periodically back up information
Recover a database after a failure
Security management
Who has access to what information
Who can perform CRUD tasks on information

40. Data Administration Subsystem
Query optimization
Restructure physical view to optimize response times to queries
Concurrency control
What happens if two people simultaneously try to change the same information?

41. 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?

42. 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

43. 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

44. What Is a Data Warehouse?

45. 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 97?

46. 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

47. What Are Data-Mining Tools?

48. 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

49. Intelligent Agents
Use various 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

50. 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

51. Statistical Tools
Help you apply various mathematical models to the information stored in a data warehouse to discover new information
Regression
Analysis of variance
And so on

52. 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

53. Data Marts

54. 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

55. Considerations in Using a Data Warehouse
Do you need a data warehouse?
DBMS may offer all you need
Do all employees need the entire data warehouse?
Consider a data mart
How up-to-date must information be?
“Snapshot” concept
What data-mining tools do you need?
Training can be expensive

56. INFORMATION OWNERSHIP
Strategic management support
The sharing of information with responsibility
Information cleanliness

57. 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

58. Strategic Management Support
Data administration – plans for, oversees the development of, and monitors the information resource
Database administration – responsible for the more technical aspects and operational aspects of managing information
Both often report to the CIO

59. The Sharing of Information with Responsibility
If you create it, you “own” it
You will also share it with others
Because you “own” it, you are responsible for its quality

60. Information Cleanliness
Database and data warehouse information must be “clean”
No errors
No duplicates

61. Information Cleanliness
Extraction, transformation, and loading (ETL) – what information you want from each database, how the information is associated, and what rules to follow in consolidating the information to ensure its cleanliness in a data warehouse

62. CAN YOU…
Describe business intelligence and its role in an organization.
Differentiate between databases and data warehouses with respect to their focus on OLTP and OLAP.
List and describe the key characteristics of a relational database.

63. CAN YOU…
Define the five software components of a database management system.
List and describe the key characteristics of a data warehouse.
Define the four major types of data-mining tools in a data warehouse environment.
List key considerations in information ownership in an organization.