1. DATABASES AND DATA WAREHOUSES Searching for Revenue - Google
CHAPTER 6
DATABASES AND DATA WAREHOUSES
Opening Case
Searching for Revenue - Google

2. Chapter Six Overview SECTION 6.1 – DATABASE FUNDAMENTALS
Understanding Information
Database Fundamentals
Database Advantages
Relational Database Fundamentals
Database Management Systems
Integrating Data Among Multiple Databases
SECTION 6.2 – DATA WARAEHOUSE FUNDAMENTALS
Accessing Organizational Information
History of Data Warehousing
Data Warehouse Fundamentals
Business Intelligence
Data Mining

3. DATABASE FUNDAMENTALS
SECTION 6.1
DATABASE FUNDAMENTALS

4. LEARNING OUTCOMES
List, describe, and provide an example of each of the five characteristics of high quality information
Define the relationship between a database and a database management system
Describe the advantages an organization can gain by using a database.

5. LEARNING OUTCOMES
Define the fundamental concepts of the relational database model
Describe the role and purpose of a database management system and list the four components of a database management system
Describe the two primary methods for integrating information across multiple databases

6. UNDERSTANDING INFORMATION
Information is everywhere in an organization
Employees must be able to obtain and analyze the many different levels, formats, and granularities of organizational information to make decisions
Successfully collecting, compiling, sorting, and analyzing information can provide tremendous insight into how an organization is performing

7. UNDERSTANDING INFORMATION
Information granularity – refers to the extent of detail within the information (fine and detailed or coarse and abstract)
Levels
Formats
Granularities

8. Information Quality
Business decisions are only as good as the quality of the information used to make the decisions
Characteristics of high quality information include:
Accuracy
Completeness
Consistency
Uniqueness
Timeliness

9. Information Quality
Low quality information example

10. Understanding the Costs of Poor Information
The four primary sources of low quality information include:
Online customers intentionally enter inaccurate information to protect their privacy
Information from different systems have different entry standards and formats
Call center operators enter abbreviated or erroneous information by accident or to save time
Third party and external information contains inconsistencies, inaccuracies, and errors

11. Understanding the Costs of Poor Information
Potential business effects resulting from low quality information include:
Inability to accurately track customers
Difficulty identifying valuable customers
Inability to identify selling opportunities
Marketing to nonexistent customers
Difficulty tracking revenue due to inaccurate invoices
Inability to build strong customer relationships

12. Understanding the Benefits of Good Information
High quality information can significantly improve the chances of making a good decision
Good decisions can directly impact an organization's bottom line

13. DATABASE FUNDAMENTALS
Information is everywhere in an organization
Information is stored in databases
Database – maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)

14. DATABASE FUNDAMENTALS
Database models include:
Hierarchical database model – information is organized into a tree-like structure (using parent/child relationships) in such a way that it cannot have too many relationships
Network database model – a flexible way of representing objects and their relationships
Relational database model – stores information in the form of logically related two-dimensional tables

15. DATABASE ADVANTAGES
Database advantages from a business perspective include
Increased flexibility
Increased scalability and performance
Reduced information redundancy
Increased information integrity (quality)
Increased information security

16. Increased Flexibility
A well-designed database should:
Handle changes quickly and easily
Provide users with different views
Have only one physical view
Physical view – deals with the physical storage of information on a storage device
Have multiple logical views
Logical view – focuses on how users logically access information

17. Increased Scalability and Performance
A database must scale to meet increased demand, while maintaining acceptable performance levels
Scalability – refers to how well a system can adapt to increased demands
Performance – measures how quickly a system performs a certain process or transaction

18. Reduced Redundancy Databases reduce information redundancy
Redundancy – the duplication of information or storing the same information in multiple places
Inconsistency is one of the primary problems with redundant information

19. Increased Integrity (Quality)
Information integrity – measures the quality of information
Integrity constraint – rules that help ensure the quality of information
Relational integrity constraint – rule that enforces basic and fundamental information-based constraints
Business-critical integrity constraint – rule that enforce business rules vital to an organization’s success and often require more insight and knowledge than relational integrity constraints

20. Increased Security
Information is an organizational asset and must be protected
Databases offer several security features including:
Password – provides authentication of the user
Access level – determines who has access to the different types of information
Access control – determines types of user access, such as read-only access

21. RELATIONAL DATABASE FUNDAMENTALS
Entity – a person, place, thing, transaction, or event about which information is stored
The rows in each table contain the entities
In Figure 6.5 CUSTOMER includes Dave’s Sub Shop and Pizza Palace entities
Entity class (table) – a collection of similar entities
In Figure 6.5 CUSTOMER, ORDER, ORDER LINE, DISTRIBUTOR, and PRODUCT entity classes

22. RELATIONAL DATABASE FUNDAMENTALS
Attributes (fields, columns) – characteristics or properties of an entity class
The columns in each table contain the attributes
In Figure 6.5 attributes for CUSTOMER include:
Customer ID
Customer Name
Contact Name
Phone

23. RELATIONAL DATABASE FUNDAMENTALS
Primary keys and foreign keys identify the various entity classes (tables) in the database
Primary key – a field (or group of fields) that uniquely identifies a given entity in a table
Foreign key – a primary key of one table that appears an attribute in another table and acts to provide a logical relationship among the two tables

24. Potential relational database for Coca-Cola

25. DATABASE MANAGEMENT SYSTEMS
Database management systems (DBMS) – software through which users and application programs interact with a database

26. DATABASE MANAGEMENT SYSTEMS
Four components of a DBMS

27. Data Definition Component
Data definition component – creates and maintains the data dictionary and the structure of the database
The data definition component includes the data dictionary
Data dictionary – a file that stores definitions of information types, identifies the primary and foreign keys, and maintains the relationships among the tables

28. Data Definition Component
Data dictionary essentially defines the logical properties of the information that the database contains

29. Data Manipulation Component
Data manipulation component – allows users to create, read, update, and delete information in a database
A DBMS contains several data manipulation tools:
View – allows users to see, change, sort, and query the database content
Report generator – users can define report formats
Query-by-example (QBE) – users can graphically design the answers to specific questions
Structured query language (SQL) – query language

30. Data Manipulation Component
Sample report using Microsoft Access Report Generator

31. Data Manipulation Component
Sample report using Access Query-By-Example (QBE) tool

32. Data Manipulation Component
Results from the query in Figure 6.10

33. Data Manipulation Component
SQL version of the QBE Query in Figure 6.10

34. Application Generation and Data Administration Components
Application generation component – includes tools for creating visually appealing and easy-to-use applications
Data administration component – provides tools for managing the overall database environment by providing faculties for backup, recovery, security, and performance
IT specialists primarily use these components

35. INTEGRATING DATA AMONG MULTIPLE DATABASES
Integration – allows separate systems to communicate directly with each other
Forward integration – takes information entered into a given system and sends it automatically to all downstream systems and processes
Backward integration – takes information entered into a given system and sends it automatically to all upstream systems and processes

36. INTEGRATING DATA AMONG MULTIPLE DATABASES
Forward and backward integration

37. INTEGRATING DATA AMONG MULTIPLE DATABASES
Building a central repository specifically for integrated information

38. OPENING CASE QUESTIONS Google
How did the Web site RateMyProfessors.com solve its problem of low-quality information?
Review the five common characteristics of high-quality information and rank them in order of importance to Google’s business
What would be the ramifications to Google’s business if the search information it presented to its customers was of low quality?

39. OPENING CASE QUESTIONS Google
Describe the different types of databases. Why should Google use a relational database?
Identify the different types of entity, entity classes, attributes, keys, and relationships that might be stored in Google’s AdWords relational database

40. DATA WAREHOUSE FUNDAMENTALS
SECTION 6.2
DATA WAREHOUSE FUNDAMENTALS

41. LEARNING OUTCOMES
Describe the roles and purposes of data warehouses and data marts in an organization
Compare the multidimensional nature of data warehouses (and data marts) with the two-dimensional nature of databases

42. LEARNING OUTCOMES
Identify the importance of ensuring the cleanliness of information throughout an organization
Explain the relationship between business intelligence and a data warehouse

43. HISTORY OF DATA WAREHOUSING
Data warehouses extend the transformation of data into information
In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions
The data warehouse provided the ability to support decision making without disrupting the day-to-day operations

44. DATA WAREHOUSE FUNDAMENTALS
Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks
The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes

45. DATA WAREHOUSE FUNDAMENTALS
Extraction, transformation, and loading (ETL) – a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse
Data mart – contains a subset of data warehouse information

46. DATA WAREHOUSE FUNDAMENTALS

47. Multidimensional Analysis
Databases contain information in a series of two-dimensional tables
In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows
Dimension – a particular attribute of information

48. Multidimensional Analysis
Cube – common term for the representation of multidimensional information

49. Multidimensional Analysis
Data mining – the process of analyzing data to extract information not offered by the raw data alone
To perform data mining users need data-mining tools
Data-mining tool – uses a variety of techniques to find patterns and relationships in large volumes of information and infers rules that predict future behavior and guide decision making

50. Information Cleansing or Scrubbing
An organization must maintain high-quality data in the data warehouse
Information cleansing or scrubbing – a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information

51. Information Cleansing or Scrubbing
Contact information in an operational system

52. Information Cleansing or Scrubbing
Standardizing Customer name from Operational Systems

53. Information Cleansing or Scrubbing

54. Information Cleansing or Scrubbing
Accurate and complete information

55. BUSINESS INTELLIGENCE
Business intelligence – information that people use to support their decision-making efforts
Principle BI enablers include:
Technology
People
Culture

56. DATA MINING
Data-mining software includes many forms of AI such as neural networks and expert systems

57. DATA MINING Common forms of data-mining analysis capabilities include:
Cluster analysis
Association detection
Statistical analysis

58. Cluster Analysis
Cluster analysis – a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible
CRM systems depend on cluster analysis to segment customer information and identify behavioral traits

59. Association Detection
Association detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the information
Market basket analysis – analyzes such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services

60. Statistical Analysis
Statistical analysis – performs such functions as information correlations, distributions, calculations, and variance analysis
Forecast – predictions made on the basis of time-series information
Time-series information – time-stamped information collected at a particular frequency

61. OPENING CASE QUESTIONS Google
How could Google use a data warehouse to improve its business operations?
Why would Google need to scrub and cleanse the information in its data warehouse?
Identify a data mart that Google’s marketing and sales department might use to track and analyze its AdWords revenue

62. CLOSING CASE ONE Fishing for Quality
Explain the importance of high-quality information for the Alaska Department of Fish and Game
Review the five common characteristics of high quality information and rank them in order of importance for the Alaska Department of Fish and Game
How could data warehouses and data marts be used to help the Alaska Department of Fish and Game improve the efficiency and effectiveness of its operations?

63. CLOSING CASE ONE Fishing for Quality
What two data marts might the Alaska Department of Fish and Game want to build to help it analyze its operational performance?
Do the managers at the Alaska Department of Fish and Game actually have all of the information they require to make an accurate decision? Explain the statement “it is never possible to have all of the information required to make the best decision possible”

64. CLOSING CASE TWO Mining the Data Warehouse
Explain how Ben & Jerry’s is using business intelligence tools to remain successful and competitive in a saturated market
Identify why information cleansing and scrubbing is critical to California Pizza Kitchen’s business intelligence tool’s success

65. CLOSING CASE TWO Mining the Data Warehouse
Illustrate why 100 percent accurate and complete information is impossible for Noodles & Company to obtain
Describe how each of the companies above is using BI from their data warehouse to gain a competitive advantage

66. CLOSING CASE THREE Harrah’s
Identify the effects poor information might have on Harrah’s service-oriented business strategy
How does Harrah’s uses database technologies to implement its service-oriented strategy?
Harrah’s was one of the first casino companies to find value in offering rewards to customers who visit multiple Harrah’s locations. Describe the effects on the company if it did not build any integrations among the databases located at each of its casinos

67. CLOSING CASE THREE Harrah’s
Estimate the potential impact to Harrah’s business if there is a security breach in its customer information
Identify three different types of data marts Harrah’s might want to build to help it analyze its operational performance

68. CLOSING CASE THREE Harrah’s
What might occur if Harrah’s fails to clean or scrub its information before loading it into its data warehouse?
Describe cluster analysis, association detection, and statistical analysis and explain how Harrah’s could use each one to gain insights into its business