1 Fundamentals of Information Systems, Seventh EditionChapter 3 Data Centers, and Business Intelligence Fundamentals of Information Systems, Seventh Edition

2 Fundamentals of Information Systems, Seventh EditionThe Database Approach The database approach: Traditional approach to data management: Each distinct operational system used data files dedicated to that system Database approach to data management: Pool of related data is shared by multiple application programs the Database Approach At one time, information systems referenced specific files containing relevant data. For example, a payroll system would use a payroll file. Each distinct operational system used data files dedicated to that system. This approach to data management is called the traditional approach to data management. Today, most organizations use the database approach to data management, whereby multiple information systems share a pool of related data. A database offers the ability to share data and information resources. Federal databases, for example, often include the results of DNA tests as an attribute for convicted criminals. The information can be shared with law enforcement officials around the country. To use the database approach to data management, additional software—a database management system (DBMS)—is required. As previously discussed, a DBMS consists of a group of programs that can be used as an interface between a database and the user of the database. Typically, this software acts as a buffer between the application programs and the database itself. Figure 3.4 illustrates the database approach. Table 3.1 lists some of the primary advantages of the database approach, and Table 3.2 lists some disadvantages. key A field or set of fields in a record that is used to identify the record. primary key A field or set of fields that uniquely identifies the record. traditional approach to data management An approach to data management whereby each distinct operational system used data files dedicated to that system. database approach to data management An approach to data management whereby a pool of related data is shared by multiple information systems. Database Systems, Data Centers, and Business Intelligence | Chapter Copyright 2011 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Fundamentals of Information Systems, Seventh Edition

3 Traditional approach to data managementFundamentals of Information Systems, Seventh Edition

4 The Database Approach (continued)Check Table 3.1 Advantages of the Database Approach Fundamentals of Information Systems, Seventh Edition

5 Data Centers, Data Modeling and Database CharacteristicsWhen building a database, an organization must consider: Content: What data should be collected and at what cost? Access: What data should be provided to which users and when? Logical structure: How should data be arranged so that it makes sense to a given user? Physical organization: Where should data be physically located? Because today’s businesses have so many elements, they must keep data organized so that it can be used effectively. A database should be designed to store all data relevant to the business and provide quick access and easy modification. Moreover, it must reflect the business processes of the organization. When building a database, an organization must carefully consider these questions: • Content. What data should be collected and at what cost? • Access. What data should be provided to which users and when? • Logical structure. How should data be arranged so that it makes sense to a given user? • Physical organization. Where should data be physically located? The U.S. federal government carefully considers what information it should make accessible and what information should remain private. The Bush administration kept a great deal of information private during the years following the bombing of the Twin Towers in New York City. When President Obama took office, he pledged to run a much more transparent government. He followed through with his promise by providing access to hundreds of government databases through the Web site News agencies, research labs, and analysts can use this Web site to connect databases directly to government records to track government actions and information.8 Fundamentals of Information Systems, Seventh Edition

6 Fundamentals of Information Systems, Seventh EditionData Center Climate-controlled building or set of buildings that house database servers and the systems that deliver mission-critical information and services Traditional data centers: Consist of warehouses filled with row upon row of server racks and powerful cooling systems Data Center Databases, and the systems that manipulate them, can be physically stored on computers as small as a PC or as large as mainframes and data centers. A data center is a climate-controlled building or set of buildings that house database servers and the systems that deliver missioncritical information and services. Data centers of large organizations are often distributed among several locations, but a recent trend has many organizations consolidating their data centers into a few large facilities. For example, the U.S. federal government is working to save billions of dollars by consolidating 1,100 data centers into a dozen facilities. The project is recognized as the largest data center consolidation in history.9 The state of Texas is in the midst of a seven-year effort to consolidate its 31 data centers into two facilities in San Angelo and Austin.10 Microsoft recently constructed a $550 million, 400,000-square-foot data center on 44 acres in San Antonio. Google invested $600 million for a mega data center in Lenoir, North Carolina, and $750 million for another in Goose Creek, South Carolina. Clearly, storing and managing data is a serious business. Traditional data centers consist of warehouses filled with row upon row of server racks and powerful cooling systems to compensate for the heat generated by the processors. Microsoft,11 Google,12 and others have adopted a new modular data center approach, which uses large shipping containers like the ones that transport consumer goods around the world. The huge containers, such as the HP POD, are packed with racks of servers prewired and cooled to easily connect and set up. Microsoft recently constructed a 700,000-square-foot data center in Northlake, Illinois. It is considered to be one of the largest in the world, taking up 16 football fields of space. The mega facility is filled with 220 shipping containers packed with servers. Microsoft says that a new shipping container can be wheeled into place and connected to the Internet within hours.13 See Figure 3.6 Fundamentals of Information Systems, Seventh Edition

7 Data Center (continued)Many organizations now use large shipping containers packed with racks of servers and cooled to easily connect and set up Businesses and technology vendors working to develop green data centers that run more efficiently and require less energy for processing and cooling Backup and security procedures for data centers can be a concern . Microsoft,11 Google,12 and others have adopted a new modular data center approach, which uses large shipping containers like the ones that transport consumer goods around the world. The huge containers, such as the HP POD, are packed with racks of servers prewired and cooled to easily connect and set up. Microsoft recently constructed a 700,000-square-foot data center in Northlake, Illinois. It is considered to be one of the largest in the world, taking up 16 football fields of space. The mega facility is filled with 220 shipping containers packed with servers. Microsoft says that a new shipping container can be wheeled into place and connected to the Internet within hours are approaching the point of automation, whereby they can run and manage themselves while being monitored remotely. This is referred to as a “lights out” environment. The State of Vermont recently switched to a lights out approach for nights and weekends, reducing its staff by 40 percent and significantly reducing costs.15 HP has moved to automated data centers, reducing its IT staffing needs by 3, As data centers continue to expand in terms of the quantity of data that they store and process, their energy demands are becoming an increasingly significant portion of the total energy demands of humanity. Businesses and technology vendors are working to develop green data centers that run more efficiently and require less energy for processing and cooling Modular data centers are becoming popular around the world due to their convenience and efficiencies. Taiwan’s Technology Research Institute is working to create standards for modular data centers in shipping containers that they say will reduce the costs of these units by half while increasing ease of use and reducing energy demands.14 While a company’s data sits in large supercooled data centers, the people accessing that data are typically in offices spread across the country or around the world. In fact, the expectation of data center specialists such as Hewlett-Packard CEO Mark Hurd is that in the near future, the only personnel on duty at data centers will be security guards. Data centers Fundamentals of Information Systems, Seventh Edition

8 Fundamentals of Information Systems, Seventh EditionData Modeling Data model: Diagram of data entities and their relationships Enterprise data modeling: Starts by investigating the general data and information needs of the organization at the strategic level Entity-relationship (ER) diagrams: Data models that use basic graphical symbols to show the organization of and relationships between data Data Modeling When organizing a database, key considerations include determining what data to collect, who will have access to it, and how they might want to use it. After determining these details, an organization can create the database. Building a database requires two different types of designs: a logical design and a physical design. The logical design of a database is an abstract model of how the data should be structured and arranged to meet an organization’s information needs. The logical design involves identifying relationships among the data items and grouping them in an orderly fashion. Because databases provide both input and output for information systems throughout a business, users from all functional areas should assist in creating the logical design to ensure that their needs are identified and addressed. The physical design starts from the logical database design and fine-tunes it for performance and cost considerations (such as improved response time, reduced storage space, and lower operating cost). The person who fine-tunes the physical design must have an in-depth knowledge of the DBMS. For example, the logical database design might need to be altered so that certain data entities are combined, summary totals are carried in the data records rather than calculated from elemental data, and some data attributes are repeated in more than one data entity. These are examples of planned data redundancy, which is done to improve the system performance so that user reports or queries can be created more quickly. One of the tools database designers use to show the logical relationships among data is a data model. A data model is a diagram of entities and their relationships. Data modeling usually involves understanding a specific business problem and analyzing the data and information needed to deliver a solution. When done at the level of the entire organization, this is called enterprise data modeling. Enterprise data modeling is an approach that starts by investigating the general data and information needs of the organization at the strategic level, and then examines more specific data and information needs for the various functional areas and departments within the organization. Various models have been developed to help managers and database designers analyze data and information needs. An entity-relationship diagram is an example of such a data model. Entity-relationship (ER) diagrams use basic graphical symbols to show the organization of and relationships between data. In most cases, boxes in ER diagrams indicate data items or entities contained in data tables, and diamonds show relationships between data items and entities. In other words, ER diagrams show data items in tables (entities) and the ways they are related. ER diagrams help ensure that the relationships among the data entities in a database are correctly structured so that any application programs developed are consistent with business operations and user needs. In addition, ER diagrams can serve as reference documents after a database is in use. If changes are made to the database, ER diagrams help design them. Fundamentals of Information Systems, Seventh Edition

9 Fundamentals of Information Systems, Seventh EditionFigure 3.7 shows an ER diagram for an order database. In this database design, one salesperson serves many customers. This is an example of a one-to-many relationship, as indicated by the one-to-many symbol (the “crow’s-foot”) shown in Figure 3.7. The ER diagram also shows that each customer can place one-to-many orders; each order includes one-to-many line items; and many line items can specify the same product (a many-to-one relationship). This database can also have one-to-one relationships. For example, one order generates one invoice Fundamentals of Information Systems, Seventh Edition

10 The Relational Database ModelRelational model: Describes data using a standard tabular format Each row of a table represents a data entity (record) Columns of the table represent attributes (fields) The domain is the range of allowable values for data attributes Although there are a number of different database models, including flat files, hierarchical, and network models, the relational model has become the most popular, and use of this model will continue to increase. The relational model describes data using a standard tabular format; all data elements are placed in two-dimensional tables, called relations, which are the logical equivalent of files. The tables in relational databases organize data in rows and columns, simplifying data access and manipulation. It is normally easier for managers to understand the relational model than other database models. relational model A database model that describes data in which all data elements are placed in two-dimensional tables, called relations, which are the logical equivalent of files. A Relational Database Model In the relational model, all data elements are placed in twodimensional tables, or relations. As long as they share at least one common element, these relations can be linked to output useful information. Databases based on the relational model include IBM DB2, Oracle, Sybase, Microsoft SQL Server, Microsoft Access, and MySQL. Oracle is currently the market leader in generalpurpose databases, with about half of the multibillion dollar database market. Oracle’s most recent edition of its relational database, 11g, is highly sophisticated and uses database grids that allow a single database to run across a cluster of computers.17 In the relational model, each row of a table represents a data entity—a record—and each column of the table represents an attribute—a field. Each attribute can accept only certain values. The allowable values for these attributes are called the domain. The domain for a particular attribute indicates what values can be placed in each column of the relational table. For instance, the domain for an attribute such as gender would be limited to male or female. A domain for pay rate would not include negative numbers. In this way, defining a domain can increase data accuracy Fundamentals of Information Systems, Seventh Edition

11 Fundamentals of Information Systems, Seventh Edition

12 The Relational Database Model (continued)Data cleanup Process of looking for and fixing inconsistencies to ensure that data is accurate and complete Database normalization is often used to clean up problems with data from slide Fundamentals of Information Systems, Seventh Edition

13 Database Management SystemsCreating and implementing the right database system ensures that the database will support both business activities and goals Capabilities and types of database systems vary considerably DATABASE MANAGEMENT SYSTEMS Creating and implementing the right database system ensures that the database will support both business activities and goals. But how do we actually create, implement, use, and update a database? The answer is found in the database management system. As discussed earlier, a DBMS is a group of programs used as an interface between a database and application programs or a database and the user. The capabilities and types of database systems, however, vary considerably. For example, Twitter, Google, Brightkite, and other Internet companies that provide GPS location applications are discussing the creation of a “Unified Database of Places.” Rather than each company building proprietary databases of business and attraction locations, they would like to pool resources to build one huge database of places that includes details on every location on earth; such data would fuel applications like Google Street View.18 Indeed, DBMSs are used to manage all kinds of data for all kinds of purpose Fundamentals of Information Systems, Seventh Edition

14 Overview of Database TypesFlat file Simple database program whose records have no relationship to one another Single user Only one person can use the database at a time Examples: Access, FileMaker Pro, and InfoPath Multiple users Allow dozens or hundreds of people to access the same database system at the same time Examples: Oracle, Microsoft, Sybase, and IBM Overview of Database Types Database management systems can range from small, inexpensive software packages to sophisticated systems costing hundreds of thousands of dollars. The following sections discuss a few popular alternatives. See Figure 3.12 for one example. Flat File A flat file is a simple database program whose records have no relationship to one another. Flat file databases are often used to store and manipulate a single table or file; they do not use any of the database models discussed previously, such as the relational model. Many spreadsheet and word-processing programs have flat file capabilities. These software packages can sort tables and make simple calculations and comparisons. Microsoft OneNote is designed to let people put ideas, thoughts, and notes into a flat file. In OneNote, each note can be placed anywhere on a page or in a box on a page, called a container. Pages are organized into sections and subsections that appear as colored tabs. After you enter a note, you can retrieve, copy, and paste it into other applications, such as word-processing and spreadsheet programs. ResMed, a medical firm that manufactures products to assist people with respiratory conditions, uses OneNote to collect new ideas for product improvements and track the status of those ideas through evaluation and implementation.19 OneNote assists the company in its efforts to increase participation in reducing costs and becoming more efficient Similar to OneNote, EverNote is a free online database service that can store notes and other pieces of information. Considering the amount of information today’s high-capacity hard disks can store, the popularity of databases that can handle unstructured data will continue to grow. Single User A database installed on a personal computer is typically meant for a single user. Microsoft Office Access and FileMaker Pro are designed to support single-user implementations. Microsoft InfoPath is another example of a database program that supports a single user. This software is part of the Microsoft Office suite, and it helps people collect and organize information from a variety of sources. InfoPath has built-in forms that can be used to enter expense information, timesheet data, and a variety of other information. Multiple Users Small, midsize, and large businesses need multiuser DBMSs to share information throughout the organization over a network. These more powerful, expensive systems allow dozens or hundreds of people to access the same database system at the same time. Popular vendors for multiuser database systems include Oracle, Microsoft, Sybase, and IBM. Many single-user databases, such as Microsoft Access, can be implemented for multiuser support over a network, though they often are limited in the number of users they can support. All DBMSs share some common functions, such as providing a user view, physically storing and retrieving data in a database, allowing for database modification, manipulating data, and generating reports. These DBMSs can handle the most complex data-processing tasks, and because they are accessed over a network, one database can serve many locations around the world. For example, the Linde Group is a global leader in industrial gases and hydrogen production. Its 50,000 employees, spread across 100 countries, all access a central database stored in a data center in Munich, Germany. Fundamentals of Information Systems, Seventh Edition

15 Storing and Retrieving DataWhen an application program needs data it requests the data through the DBMS Concurrency control deals with the situation in which two or more users or applications need to access the same record at the same time Storing and Retrieving Data One function of a DBMS is to be an interface between an application program and the database. When an application program needs data, it requests the data through the DBMS. Suppose that to calculate the total price of a new car, a pricing program needs price data on the engine option—six cylinders instead of the standard four cylinders. The application program requests this data from the DBMS. In doing so, the application program follows a logical access path. Next, the DBMS, working with various system programs, accesses a storage device, such as disk drives, where the data is stored. When the DBMS goes to this storage device to retrieve the data, it follows a path to the physical location (physical access path) where the price of this option is stored. In the pricing example, the DBMS might go to a disk drive to retrieve the price data for six-cylinder engines. This relationship is shown in Figure This same process is used if a user wants to get information from the database. First, the user requests the data from the DBMS. For example, a user might give a command, such as LIST ALL OPTIONS FOR WHICH PRICE IS GREATER THAN 200 DOLLARS. This is the logical access path (LAP). Then, the DBMS might go to the options price section of a disk to get the information for the user. This is the physical access path (PAP) Fundamentals of Information Systems, Seventh Edition

16 Fundamentals of Information Systems, Seventh EditionTwo or more people or programs attempting to access the same record at the same time can cause a problem. For example, an inventory control program might attempt to reduce the inventory level for a product by ten units because ten units were just shipped to a customer. At the same time, a purchasing program might attempt to increase the inventory level for the same product by 200 units because inventory was just received. Without proper database control, one of the inventory updates might be incorrect, resulting in an inaccurate inventory level for the product. Concurrency control can be used to avoid this potential problem. One approach is to lock out all other application programs from access to a record if the record is being updated or used by another program Fundamentals of Information Systems, Seventh Edition

17 Manipulating Data and Generating Reports (continued)Structured query language (SQL): Adopted by the American National Standards Institute (ANSI) as the standard query language for relational databases Once a database has been set up and loaded with data, it can produce reports, documents, and other outputs Only from slide Fundamentals of Information Systems, Seventh Edition

18 Database AdministrationDBA: Works with users to decide the content of the database Works with programmers as they build applications to ensure that their programs comply with database management system standards and conventions Data administrator: Responsible for defining and implementing consistent principles for a variety of data issues Database Administration Database systems require a skilled database administrator (DBA), who is expected to have a clear understanding of the fundamental business of the organization, be proficient in the use of selected database management systems, and stay abreast of emerging technologies and new design approaches. The role of the DBA is to plan, design, create, operate, secure, monitor, and maintain databases. Typically, a DBA has a degree in computer science or management information systems and some on-the-job training with a particular database product or more extensive experience with a range of database products. The DBA works with users to decide the content of the database—to determine exactly what entities are of interest and what attributes are to be recorded about those entities. Thus, personnel outside of IS must have some idea of what the DBA does and why this function is important. The DBA can play a crucial role in the development of effective information systems to benefit the organization, employees, and managers. The DBA also works with programmers as they build applications to ensure that their programs comply with database management system standards and conventions. After the database is built and operating, the DBA monitors operations logs for security violations. Database performance is also monitored to ensure that the system’s response time meets users’ needs and that it operates efficiently. If there is a problem, the DBA attempts to correct it before it becomes serious. A database failure can cause huge financial losses for a business. A failure due to mechanical problems, controller failures, viruses or attacks, or human failure can cause productivity in an organization to grind to a halt Fundamentals of Information Systems, Seventh Edition

19 Popular Database Management SystemsPopular DBMSs for end users: Microsoft’s Access and FileMaker Pro Number of open source DBMS including PostgreSQL, MySQL, and CouchDB from slide only Fundamentals of Information Systems, Seventh Edition

20 Database VirtualizationUses virtual servers and operating systems to allow two or more database systems, including servers and DBMSs to act like a single, unified database system Allows more efficient use of computing resources, reduce costs, and provide better access to critical information Extra informations (read only ) Virtualization enables compute and storage resources to be pooled and allocated on demand. This enables both the sharing of single server resources for multi-tenancy, as well as the pooling of server resources into a single logical database or cluster. In both cases, database virtualization provides increased flexibility, more granular and efficient allocation of pooled resources, and more scalable computing Fundamentals of Information Systems, Seventh Edition

21 Using Databases with Other SoftwareDBMSs can act as front-end or back-end applications: Front-end applications interact directly with people Back-end applications interact with other programs or applications Only From slide Fundamentals of Information Systems, Seventh Edition

22 Data Warehouses, Data Marts, and Data MiningDatabase that holds business information from many sources in the enterprise Data mart Subset of a data warehouse Data mining Information-analysis tool that involves the automated discovery of patterns and relationships in a data warehouse Data Warehouses A data warehouse is a database that holds business information from many sources in the enterprise, covering all aspects of the company’s processes, products, and customers. The data warehouse provides business users with a multidimensional view of the data they need to analyze business conditions. Data warehouses allow managers to drill down to get more detail or roll up to take detailed data and generate aggregate or summary reports. A data warehouse is designed specifically to support management decision making, not to meet the needs of transaction processing systems. A data warehouse stores historical data that has been extracted from operational systems and external data sources. See Figure This operational and external data is “cleaned up” to remove inconsistencies and integrated to create a new information database that is more suitable for business analysis data warehouse A large database that collects business information from many sources in the enterprise, covering all aspects of the company’s processes, products, and customers, in support of management decision making Data warehouses typically start out as very large databases, containing millions and even hundreds of millions of data records. As this data is collected from the various production systems, a historical database is built that business analysts can use to track changes in an organization over time and analyze current conditions. To keep it fresh and accurate, the data warehouse receives regular updates. Old data that is no longer needed is purged from the data warehouse. Updating the data warehouse must be fast, efficient, and automated, or the ultimate value of the data warehouse is sacrificed. It is common for a data warehouse to contain from three to ten years of current and historical data. Data-cleaning tools can merge data from many sources into one database, automate data collection and verification, delete unwanted data, and maintain data in a database management system. Data warehouses can also acquire data from unique sources. Oracle’s Warehouse Management software, for example, can accept information from Radio Frequency Identification (RFID) technology, which is being used to tag products as they are shipped or moved from one location to another. Honda Italia, the world leader in powered two-wheel vehicle manufacturing, uses RFID to feed its data warehouse with information about production. Each vehicle component is tagged with an RFID chip so it can be tracked through the entire production process. The RFID-based system provides highly detailed information to production managers who can tweak production to quickly identify problems and improve supply with little or no wasted effort or resources.28 The primary advantage of data warehousing is the ability to relate data in innovative ways. However, a data warehouse for a large organization can be extremely difficult to establish, with the typical cost exceeding $2 million. Data Marts A data mart is a subset of a data warehouse. Data marts bring the data warehouse concept—online analysis of sales, inventory, and other vital business data that has been gathered from transaction processing systems—to small and medium-sized businesses and to departments within larger companies. Rather than store all enterprise data in one monolithic database, data marts contain a subset of the data for a single aspect of a company’s business—for example, finance, inventory, or personnel. In fact, a specific area in the data mart might contain more detailed data than the data warehouse. Data marts are most useful for smaller groups who want to access detailed data. A warehouse contains summary data that can be used by an entire company. Because data marts typically contain tens of gigabytes of data, as opposed to the hundreds of gigabytes in data warehouses, they can be deployed on less powerful hardware with smaller secondary storage devices, delivering significant savings to an organization. Although any database software can be used to set up a data mart, some vendors deliver specialized software designed and priced specifically for data marts. Companies such as Sybase, Software AG, Microsoft, and others have products and services that make it easier and cheaper to deploy these scaled-down data warehouses. The selling point: data marts put targeted business information into the hands of more decision makers. For example, the U.S. Department of Defense has created the Defense Health Services Systems' Clinical Data Mart (CDM) to deliver medical information to the more than 9 million military personnel worldwide. The system was developed in response to President Obama’s call to “raise health care quality at lower costs.”30 Data Mining Data mining is an information-analysis tool that involves the automated discovery of patterns and relationships in a data warehouse. Like gold mining, data mining sifts through mountains of data to find a few nuggets of valuable information. For example, Brooks Brothers, the oldest clothing retailer in the U.S., uses data mining to provide store managers with reports that help improve store performance and customer satisfaction.31 Data mining’s objective is to extract patterns, trends, and rules from data warehouses to evaluate (i.e., predict or score) proposed business strategies, which will improve competitiveness, increase profits, and transform business processes. It is used extensively in marketing to improve customer retention; cross-selling opportunities; campaign management; market, channel, and pricing analysis; and customer segmentation analysis (especially one-to-one marketing). In short, data-mining tools help users find answers to questions they haven’t thought to ask. data mining An information-analysis tool that involves the automated discovery of patterns and relationships in a data warehouse Fundamentals of Information Systems, Seventh Edition

23 Fundamentals of Information Systems, Seventh Editionfor explanation only Fundamentals of Information Systems, Seventh Edition

24 Business IntelligenceInvolves gathering enough of the right information: In a timely manner and usable form and analyzing it to have a positive impact on business strategy, tactics, or operations Competitive intelligence: Limited to information about competitors and the ways that knowledge affects strategy, tactics, and operations Business Intelligence The use of databases for business-intelligence purposes is closely linked to the concept of data mining. Business intelligence (BI) involves gathering enough of the right information in a timely manner and usable form and analyzing it so that it can have a positive effect on business strategy, tactics, or operations. IMS Health, for example, provides a BI system designed to assist businesses in the pharmaceutical industry with custom marketing to physicians, pharmacists, nurses, consumers, government agencies, and nonprofit healthcare organizations.34 BI turns data into useful information that is then distributed throughout an enterprise. It provides insight into the causes of problems and, when implemented, can improve business operations. For example, Puma North America, manufacturer of athletic footwear, uses SPSS software to provide business intelligence to its sales consultants. Puma’s 70 independent sales consultants depend on SPSS for the information they need to make business decisions regarding orders, shipments, and product availability.35 Competitive intelligence is one aspect of business intelligence and is limited to information about competitors and the ways that knowledge affects strategy, tactics, and operations. Competitive intelligence is a critical part of a company’s ability to see and respond quickly and appropriately to the changing marketplace. Competitive intelligence is not espionage—the use of illegal means to gather information. In fact, almost all the information a competitive-intelligence professional needs can be collected by examining published information sources, conducting interviews, and using other legal, ethical methods. Using a variety of analytical tools, a skilled competitive-intelligence professional can by deduction fill the gaps in information already gathered. The term counterintelligence describes the steps an organization takes to protect information sought by “hostile” intelligence gatherers. One of the most effective counterintelligence measures is to define “trade secret” information relevant to the company and control its dissemination. business intelligence (BI) The process of gathering enough of the right information in a timely manner and usable form and analyzing it to have a positive impact on business strategy, tactics, or operations. competitive intelligence One aspect of business intelligence limited to information about competitors and the ways that knowledge affects strategy, tactics, and operations. counterintelligence The steps an organization takes to protect information sought by “hostile” intelligence gatherers Fundamentals of Information Systems, Seventh Edition

25 Business Intelligence (continued)Counterintelligence: Steps organization takes to protect information sought by “hostile” intelligence gatherers The term counterintelligence describes the steps an organization takes to protect information sought by “hostile” intelligence gatherers. One of the most effective counterintelligence measures is to define “trade secret” information relevant to the company and control its dissemination Fundamentals of Information Systems, Seventh Edition

26 Distributed DatabasesDatabase in which the data may be spread across several smaller databases connected via telecommunications devices Gives corporations more flexibility in how databases are organized and used Replicated database: Holds a duplicate set of frequently used data Distributed Databases Distributed processing involves placing processing units at different locations and linking them via telecommunications equipment. A distributed database—a database in which the data can be spread across several smaller databases connected through telecommunications devices—works on much the same principle. A user in the Milwaukee branch of a clothing manufacturer, for example, might make a request for data that is physically located at corporate headquarters in Milan, Italy. The user does not have to know where the data is physically stored. See Figure Distributed databases give corporations and other organizations more flexibility in how databases are organized and used. Local offices can create, manage, and use their own databases, and people at other offices can access and share the data in the local databases. Giving local sites more direct access to frequently used data can improve organizational effectiveness and efficiency significantly. The New York City Police Department, for example, has thousands of officers searching for information located on servers in offices around the city. Despite its advantages, distributed processing creates additional challenges in integrating different databases (information integration), maintaining data security, accuracy, timeliness, and conformance to standards. Distributed databases allow more users direct access at different sites; however, controlling who accesses and changes data is sometimes difficult. Also, because distributed databases rely on telecommunications lines to transport data, access to data can be slower. To reduce telecommunications costs, some organizations build a replicated database. A replicated database holds a duplicate set of frequently used data. The company sends a copy of important data to each distributed processing location when needed or at predetermined times. Each site sends the changed data back to update the main database on an update cycle that meets the needs of the organization. This process, often called data synchronization, is used to make sure that replicated databases are accurate, up to date, and consistent with each other. A railroad, for example, can use a replicated database to increase punctuality, safety, and reliability. The primary database can hold data on fares, routings, and other essential information. The data can be continually replicated and downloaded on a read-only basis from the master database to hundreds of remote servers across the country. The remote locations can send back to the main database the latest figures on ticket sales and reservations. distributed database A database in which the data can be spread across several smaller databases connected via telecommunications devices. replicated database A database that holds a duplicate set of frequently used data. Fundamentals of Information Systems, Seventh Edition

27 Fundamentals of Information Systems, Seventh EditionSummary Traditional file-oriented applications are often characterized by program-data dependence The relational model places data in two-dimensional tables Fundamentals of Information Systems, Seventh Edition

28 Fundamentals of Information Systems, Seventh EditionSummary (continued) A DBMS is a group of programs used as an interface between a database and its users and other application programs DBMS basic functions include: Providing user views Creating and modifying the database Storing and retrieving data Manipulating data and generating reports Fundamentals of Information Systems, Seventh Edition

29 Fundamentals of Information Systems, Seventh EditionSummary (continued) Database virtualization allows organizations to use computing resources more efficiently, reduce costs, and provide better data access Database administrator plans, designs, operates, secures, monitors, and maintains databases Fundamentals of Information Systems, Seventh Edition

30 Fundamentals of Information Systems, Seventh EditionSummary (continued) Data warehouses are relational database management systems specifically designed to support management decision making Data mining allows the automated discovery of patterns and relationships in a data warehouse Predictive analysis combines historical data with assumptions about future conditions to forecast future events Fundamentals of Information Systems, Seventh Edition

31 Fundamentals of Information Systems, Seventh EditionSummary (continued) Business intelligence is the process of getting enough of the right information in a timely manner and usable form Competitive intelligence involves information about competitors and their strategy, tactics, and operations Counterintelligence is the steps an organization takes to protect information from hostile intelligence gathers Fundamentals of Information Systems, Seventh Edition