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

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

DATABASE FUNDAMENTALS SECTION 6.1 DATABASE FUNDAMENTALS

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.

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

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

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

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

Information Quality Low quality information example

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

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

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

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)

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

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

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

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

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

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

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

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

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

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

Potential relational database for Coca-Cola

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

DATABASE MANAGEMENT SYSTEMS Four components of a DBMS

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

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

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

Data Manipulation Component Sample report using Microsoft Access Report Generator

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

Data Manipulation Component Results from the query in Figure 6.10

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

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

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

INTEGRATING DATA AMONG MULTIPLE DATABASES Forward and backward integration

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

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?

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

DATA WAREHOUSE FUNDAMENTALS SECTION 6.2 DATA WAREHOUSE FUNDAMENTALS

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

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

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

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

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

DATA WAREHOUSE FUNDAMENTALS

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

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

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

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

Information Cleansing or Scrubbing Contact information in an operational system

Information Cleansing or Scrubbing Standardizing Customer name from Operational Systems

Information Cleansing or Scrubbing

Information Cleansing or Scrubbing Accurate and complete information

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

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

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

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

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

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

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

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?

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”

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

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

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

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

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