Developing A Strategy For The Internet Age The Five Forces Model Five forces model - determines the relative attractiveness of an industry. This model was intended to be used as a tool for managers to use in deciding whether they should enter a new market or expand in the one they are already in. Buyer power - high when buyers have many choices of whom to buy from, and low when the choices are few. (Less attractive market if buyer power is high) Supplier power - high when buyers have few choices of whom to buy from, and low when there are many choices. (Less attractive market if supplier power is high) Threat of substitute products or services - low if there are very few alternatives to using the product or service. Switching costs - costs that can make customers reluctant to switch to another product or service. If there are switching costs then it is an advantage to the supplier. Threat of new entrants - high when it is easy for competitors to enter the market. Rivalry among existing competitors – An industry is less attractive to enter when the rivalry is high and more attractive when it is low. Video: porter

What is the major role of UTZ information systems? What are the characteristics of the information UTZ receives that would make it valuable? Analyze the industry that UTZ is in using the porter model, is it a good industry to be in? What competitive advantage do you feel Utz has? How does information play into that competitive advantage

Databases and Warehouses Building Business Intelligence High Tech Battles High School Truancy Using mobile technologies such as cell phones and PDAs, field attendance officers for the Boston public school system are able to access a variety of information while working in the field to deter truancy. The key isn’t necessarily the mobile technologies, but rather the powerful database that the field attendance officers access. It contains student information including address, telephone number, home room assignment, and absentee information. Armed with this information, field attendance officers are able to better focus their efforts on the students who have the most problems attending school. It’s important to discuss with your students the privacy of information at this point. If field attendance officers can wireless access student information, then it makes sense that someone could break into the system. As organizations provide greater access to information stored in databases, security and privacy will be key concerns. Why are the implementation of security and privacy measures difficult? To make good and accurate decisions and work in the most productive and efficient way, knowledge workers today need (1) access to information and (2) tools to work with that information. To support these needs, most organizations provide databases (and the DBMS tools which allow you to work with a database) and data warehouses (and the data mining tools which allow you to slice and dice your way through data warehouse information).

To make good and accurate decisions and work in the most productive and efficient way, knowledge workers today need (1) access to information and (2) tools to work with that information.

Business Intelligence What is it? Business intelligence is knowledge – knowledge about your customers, your competitors, your partners, your competitive environment, and your own internal operations Where is BI found? Databases & Data warehouses Business intelligence can be found in databases and data warehouses. To access and use that business intelligence, you use DBMSs and data mining tools, respectively.

Key Terms Online transaction processing (OLTP) – the gathering of input information, processing that information, and updating existing information to reflect the gathered and processed information. Operational database – database that supports OLTP. Online analytical processing (OLAP) the manipulation of information to support decision making. Key Term: Business intelligence is knowledge – knowledge about your customers, your competitors, your partners, your competitive environment, and your own internal operations. Key Term: Online transaction processing (OLTP) – the gathering of input information, processing that information, and updating existing information to reflect the gathered and processed information. Key Term: Operational database – database that supports OLTP. Key Term: Online analytical processing (OLAP) – the manipulation of information to support decision making. Enter bank data and upsate oltp manipulate it olap

Business Intelligence

Hierarchy of Data To understand databases, it is useful to remember that the elements of data that make up the database are divided into hierarchical levels. These logical data elements make up the foundation data concepts upon which a database is built. Character. The most basic logical element is the character, which consists of a single alphabetic, numeric, or other symbol. While it may take several bits or bytes to represent a character digitally, remember that these refer to physical storage, not the logical concept of the character itself. Field. A field is a grouping of characters that represent a characteristic of a person, place, thing, or event. A person's name is typically placed in a field. A field is a data item. A data field represents an attribute or some entity. Record. A record is a collection of interrelated fields. For example, an employee's payroll record usually contains several fields, such as their name, social security number, department, and salary. Records may be fixed-length or variable-length. File. A file is a collection of interrelated records. For example, a payroll file might contain all of the payroll files for all the employees of a firm. Files are usually classified by the application for which they are used. Database. A database is an integrated collection of logically interrelated records or files. For example, the personnel database of a firm might contain payroll, personnel action, and employee skills files. The data stored in a database is independent of the application programs using it and of the type of secondary storage devices on which it is stored.

THE RELATIONAL DATABASE MODEL A collection of information that you organize and access according to the logical structure of that information. Relational database model uses a series of logically related two-dimensional tables (called relations) or files to store information in the form of a database. Relation describes each two-dimensional table or file in the relational model. The word relation here is in reference to the collection of the data within one specific table. Created with Logical Structures (p. 130-132) Key Points: Databases are very different from spreadsheets in that you don’t have to know the physical location (i.e., row number and column character) of information you want to work with. Rather, you need only know the logical location of information. You develop the “logical” view of a database by creating a data dictionary. Data dictionary – contains the logical structure for the information.

By carefully examining the definition given to “relational databases” we can clearly identify two parts to it: Information – stored in a series of two dimensional tables, files, or relations. Logical structure of the information.

Information – stored in a series of two dimensional tables, files, or relations.

Databases are very different from spreadsheets in that you don’t have to know the physical location (i.e., row number and column character) of information you want to work with. Rather, you need only know the logical location of information. You develop the “logical” view of a database by creating a data dictionary. Logical structure of the information. In using the relational database model three distinct characteristics are important to understand: Collection of data = Information, hence logical structure Logical ties Integrity constraints To identify the information into its logical structures you need to create a data dictionary. Data dictionary - contains the logical structure for the information.

Data dictionary – contains the logical structure for the information. Integrity constraints – rules that help ensure the quality of the information.

Another key difference between spreadsheets and databases is that you must provide logical ties among the relations in a database. This is achieved by identifying primary keys, foreign keys, and relationships. Figure 3.3 on page 132 illustrates these concepts with an extended version of the Inventory database. Key Term: Primary key – a field (or group of fields in some cases) that uniquely describes each record. Key Term: Foreign key – a primary key of one file that appears in another file.

Database management system (DBMS) helps you specify the logical organization for a database and access and use (manipulating) the information within a database. A group of programs that manipulate the database and provide an interface between the database and the user of the database and other application programs

DATABASE MANAGEMENT SYSTEM TOOLS DBMS Engine Data Definition Subsystem Data Manipulation Subsystem Application Generation Subsystem Data Administration Subsystem 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 as they exist on a storage device such as a hard drive.

The DBMS Figure 3.4 Software Subsystems of a Database Management System page 85 Data definition subsystem helps you create and maintain the data dictionary and define the structure of the files in a database. In other words, the data definition subsystems allows you to create and maintain the tables (relations), relationships and constraints. Data manipulation subsystem helps you add, change, and delete information in a database and mine it for valuable information. Tools here include views, report generators, QBE, and SQL. Application generation subsystem contains facilities to help you develop transaction-intensive applications. Application generation subsystems usually include: Tools for creating visually appealing data entry screens Tools for creating easy to use data entry screens DBMS-specific programming languages Commonly used programming languages Data administration subsystem A DBMS helps you manage the overall database environment by providing facilities for backup and recovery, security management, query optimization, concurrency control, and change management.

Traditional Approach to Data Management Problems program/data dependecy High data redundancy Low data integrity

Database Approach to Data Management Moving to databases

Advantages of Database Approach Improved strategic use of corporate data Reduced data redundancy Improved data integrity Easier modification and updating Data and program independence Better access to data and information Standardization of data access Framework for program development Better overall protection of the data Shared data and information resources

Disadvantages of Database Approach Relatively high cost of purchasing and operating a DBMS in a mainframe operating environment Increased cost of specialized staff Increased vulnerability

DATA WAREHOUSES AND DATA MINING What Is a Data Warehouse? What Are Data Mining Tools? Data Marts: Smaller Data Warehouses Important Considerations in Using a Data Warehouse DATA WAREHOUSES AND DATA MINING Many organizations need information from multiple databases to solve complex problems and take advantage of large opportunities. So, they are building data warehouses and using data mining tools to extract the necessary information. Data warehouse represent the next logical step beyond databases in building business intelligence. What Is a Data Warehouse? (p. 144-145) Key Points: Data warehouses support OLAP only, not OLTP. They are multidimensional, not just two dimensions like databases. They support decision making, not transaction processing. Figure 3.8 on page 144 shows a data warehouse and its various dimensions. Key Term: Data warehouse – logical collection of information – gathered from many different operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks.

Data Warehouses and Data Mining Data Warehouses Are Multidimensional Figure 3.8 A Multidimensional Data Warehouse with Information from Multiple Operational Databases Data warehouse are: a logical collection of information gathered from many different operational databases used to create business intelligence that supports business analysis activities and decision-making tasks. Data warehouses support OLAP only, not OLTP. They are multidimensional, not just two dimensions like databases. They support decision making, not transaction processing.

Elements of a Data Warehouse Data Warehouses: A database that collects business information from many sources in the enterprise, covering all aspects of the company’s processes, products, and customers Data Warehouse Databases. These store data from current and previous years that has been extracted from the various operational and management databases of the organization. As a standardized and integrated central source of data, warehouses can be used by managers for pattern processing, where key factors and trends about operations can be identified from the historical record. Data Mart: a subset of a data warehouse Data Marts. Are subsets of the data included in a Data Warehouse which focus on specific aspects of a company, e.g. department, business process, etc.

Data Warehouses and Data Mining Data Marts – Smaller Data Warehouses Data mart - a subset of a data warehouse in which only a focused portion of the data warehouse information is kept. Data Marts Are Subsets of Data Warehouse

Data Mining: an information analysis tool that involves the automated discovery of patterns and relationships in a data warehouse Applications Market segmentation Customer churn Fraud detection Direct marketing Market basket analysis Trend analysis What Are Data Mining Tools? (p. 145-147) Key Points: Data mining tools allow you to extract information from a data warehouse. Data mining tools include query-and-reporting tools, intelligent agents, multidimensional analysis tools, and statistical tools. Figure 3.9 on page 145 illustrates the role of these various data mining tools. Key Term: Data mining tools – the software tools you use to query information in a data warehouse. Key Term: Query-and-reporting tools – similar to QBE tools, SQL, and report generators in the typical database environment. Key Term: Multidimensional analysis (MDA) tools – slice-and-dice techniques that allow you to view multidimensional information from different perspectives.

How Up-to-Date Should Data Warehouse Information Be? To adjust class sizes in a university registration system To alert people to changes in weather conditions To predict scores in professional football games To adjust radio advertisements in light of demographic changes To monitor the success of a new product line in the clothing retail industry To adjust production levels of foods in a cafeteria To switch jobs to various printers in a network – by the minute. To adjust CD rates in a bank To adjust forecasted demands of tires in an auto parts store Concept Reinforcement: Team Work – How Up-to-Date Should Data Warehouse Information Be? (p. 149) In this project, your students will evaluate a number of environments and determine how often data warehouse information should be updated – monthly, weekly, daily, or by the minute. We provide our answers below. To adjust class sizes in a university registration system – daily. To alert people to changes in weather conditions – by the minute. To predict scores in professional football games – weekly. To adjust radio advertisements in light of demographic changes – monthly. To monitor the success of a new product line in the clothing retail industry – weekly. To adjust production levels of foods in a cafeteria – by the minute. To switch jobs to various printers in a network – by the minute. To adjust CD rates in a bank – daily. To adjust forecasted demands of tires in an auto parts store – weekly.

MANAGING THE INFORMATION RESOURCE IN AN ORGANIZATION Who Should Oversee the Organization’s Information? How Will Changes in Technology Affect Organizing and Managing Information? Is Information Ownership a Consideration? What Are the Ethics Involved in Managing and Organizing Information?

OLTP and Data Warehousing

OLTP and Data Mining

Senate Democrats try to stop Pentagon data-mining project                                                                                                            Powered by                                                                    SAVE THIS | EMAIL THIS | Close    Senate Democrats try to stop Pentagon data-mining project Some conservatives also concerned about privacy issue

Databases and data warehouses clearly make it easier for people to access all kinds of information. This will lead to great debates in the area of privacy. Should organizations be left to police themselves with respect to providing access to information or should the government impose privacy legislation? Answer this question with respect to (1) customer information shared by organizations; (2) employee information shared within a specific organization; and (3) business information available to customers.

Consider that you work in the human resources management department of a local business and that many of your friends work there. Although you don’t personally generate payroll checks, you still have the ability to look up anyone’s pay. Would you check on your friends to see if they’re earning more money than you? For that matter, would you look up their pay just out of simple curiosity, knowing that you would never do anything with the information or share it with anyone else? Why or why not? People working at the Revenue Canada tax department were caught just curiously looking up the reported incomes of movie stars and other high-profile public figures. Is this acceptable? Why or why not?