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6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
6 - Foundations of BI: Database & Info Mgmt
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6 - Foundations of BI: Database & Info Mgmt

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MIS Ch6

MIS Ch6

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  • 1. Chapter 6 Foundations of Business Intelligence: Databases and Information Management6.1
  • 2. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management LEARNING OBJECTIVES • Describe how the problems of managing data resources in a traditional file environment are solved by a database management system • Describe the capabilities and value of a database management system • Apply important database design principles • Evaluate tools and technologies for accessing information from databases to improve business performance and decision making • Assess the role of information policy, data administration, and data quality assurance in the management of firm’s data resources6.2
  • 3. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Can HP Mine Success from an Enterprise Data Warehouse? • Problem: HP’s numerous systems unable to deliver the information needed for a complete picture of business operations, lack of data consistency • Solutions: Build a data warehouse with a single global enterprise-wide database; replacing 17 database technologies and 14,000 databases in use • Created consistent data models for all enterprise data and proprietary platform • Demonstrates importance of database management in creating timely, accurate data and reports • Illustrates need to standardize how data from disparate sources are stored, organized, and managed6.3
  • 4. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Organizing Data in a Traditional File Environment • File organization concepts • Computer system organizes data in a hierarchy • Field: Group of characters as word(s) or number • Record: Group of related fields • File: Group of records of same type • Database: Group of related files • Record: Describes an entity • Entity: Person, place, thing on which we store information • Attribute: Each characteristic, or quality, describing entity • E.g., Attributes Date or Grade belong to entity COURSE6.4
  • 5. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Organizing Data in a Traditional File Environment The Data Hierarchy A computer system organizes data in a hierarchy that starts with the bit, which represents either a 0 or a 1. Bits can be grouped to form a byte to represent one character, number, or symbol. Bytes can be grouped to form a field, and related fields can be grouped to form a record. Related records can be collected to form a file, and related files can be organized into a database. Figure 6-16.5
  • 6. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Organizing Data in a Traditional File Environment • Problems with the traditional file environment (files maintained separately by different departments) • Data redundancy and inconsistency • Data redundancy: Presence of duplicate data in multiple files • Data inconsistency: Same attribute has different values • Program-data dependence: • When changes in program requires changes to data accessed by program • Lack of flexibility • Poor security • Lack of data sharing and availability6.6
  • 7. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Organizing Data in a Traditional File Environment Traditional File Processing The use of a traditional approach to file processing encourages each functional area in a corporation to develop specialized applications and files. Each application requires a unique data file that is likely to be a subset of the master file. These subsets of the master file lead to data redundancy and inconsistency, processing inflexibility, and wasted storage resources. Figure 6-26.7
  • 8. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Database • Collection of data organized to serve many applications by centralizing data and controlling redundant data • Database management system • Interfaces between application programs and physical data files • Separates logical and physical views of data • Solves problems of traditional file environment • Controls redundancy • Eliminates inconsistency • Uncouples programs and data • Enables organization to central manage data and data security6.8
  • 9. Advantages DBMS6.9
  • 10. Better Data Accessibility • DBMS allows on-line access by users by providing query languages that permit users to ask questions and obtain information rather then waiting for programmers.6.10
  • 11. Economy of scale • When all the organization’s data requiremnets are satisfied by oen data base instead of many separate files, the size of the combined operation provides several advantages, like , the portion of the budget that would ordinarily be allocated to various departments for their data design,storage and maintenance costs can be pooled, possibly resources may be used to purchase a more sophisticated and powerful system than any department could afford individually. Programming time that would ordinarily be devoted to designing fiels can be spent on improving that database.6.11
  • 12. More Control Over Concurrency • In a file system if two users are permitted to access data simultaneously or both attempt to perform updates, they wil interfere with each other and one might overwrite the value recorded by the other. A DBMS have subsystems to control concurrency so that transactions are not lost or performed incorrectly.6.12
  • 13. Better Backup & Recovery Procedure • A backup tape is maintained in a databse environment which is supplemented by a lot of changes. Whenever the data base is modified, a log entry is made. If the system fails, the tape and log are used to bring he data in original state it was in before failure.6.13
  • 14. Disadvantages of Database6.14
  • 15. High Cost of DBMS • Because a complete DBMS is a very large and sophisticated piece of software, it is expensive to purchase or lease/rent.6.15
  • 16. High Hardware Cost • Additional memory and processing power may be required to run the DBMS, resulting in the need to upgrade the hardware.6.16
  • 17. High Programming Cost • Because a DBMS is a complex tool with many features. It requires experienced programmers with through knowledge resulting in extra payment for their hire and expertise.6.17
  • 18. High Conversion Costs • When an organization converts to a data base system, data has to be removed from files and loaded into the database which may be difficult and time consuming process.6.18
  • 19. Slower processing in some applications • Although integrated database in desinged to provide better information, certain applications may be slower due to the integration of data.6.19
  • 20. Increased Vulnerabilities ( Central Dependency) • Since all applications depend on database system, the failure or any component can bring operations to a standstill.6.20
  • 21. More Difficult Recovery • The recovery process after a system failure is more complicated because the system must determine which transactions were completed and which were in progress at the time of failure. The fact that a database allows users to make updated concurrently further complicated the recovery the recovery process.6.21
  • 22. When not to use a DBMS • Main Costs of using a DBMS • High initial investment in hardware, software, training • Overhead for providing generality, secutiry recovery, integrity and concurrency control. • Generality that a DBMS provides for defining and processing data….6.22
  • 23. …. • When a DBMS may be unnecessary • If the database and applications are simple, well defined, and not expected to change. • If there are stringent real-time requirements that may not be met because of DBMS overhead. • If access to data by multiple users is not required.6.23
  • 24. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Human Resources Database with Multiple Views A single human resources database provides many different views of data, depending on the information requirements of the user. Illustrated here are two possible views, one of interest to a benefits specialist and one of interest to a member of the company’s payroll department. Figure 6-36.24
  • 25. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Relational DBMS • Represent data as two-dimensional tables called relations or files • Each table contains data on entity and attributes • Table: grid of columns and rows • Rows (tuples): Records for different entities • Fields (columns): Represents attribute for entity • Key field: Field used to uniquely identify each record • Primary key: Field in table used for key fields • Foreign key: Primary key used in second table as look-up field to identify records from original table6.25
  • 26. The goal of a relation database design The goal is to generate a set of relation schemes that allow us to store information without redundant data and allow us to retrieve information easily and efficiently. The approach followed is to design schemes that are in an appropriate form one of the so called Normal Form.6.26 2-26
  • 27. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Relational Database Tables A relational database organizes data in the form of two-dimensional tables. Illustrated here are tables for the entities SUPPLIER and PART showing how they represent each entity and its attributes. Supplier_Number is a primary key for the SUPPLIER table and a foreign key for the PART table. Figure 6-4A6.27
  • 28. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Relational Database Tables (cont.) Figure 6-4B6.28
  • 29. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Operations of a Relational DBMS • Three basic operations used to develop useful sets of data • SELECT: Creates subset of data of all records that meet stated criteria • JOIN: Combines relational tables to provide user with more information than available in individual tables • PROJECT: Creates subset of columns in table, creating tables with only the information specified6.29
  • 30. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management The Three Basic Operations of a Relational DBMS The select, project, and join operations enable data from two different tables to be combined and only selected attributes to be displayed. Figure 6-56.30
  • 31. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Object-Oriented DBMS (OODBMS) • Stores data and procedures as objects • Capable of managing graphics, multimedia, Java applets • Relatively slow compared with relational DBMS for processing large numbers of transactions • Hybrid object-relational DBMS: Provide capabilities of both OODBMS and relational DBMS6.31
  • 32. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Capabilities of Database Management Systems • Data definition capability: Specifies structure of database content, used to create tables and define characteristics of fields • Data dictionary: Automated or manual file storing definitions of data elements and their characteristics • Data manipulation language: Used to add, change, delete, retrieve data from database • Structured Query Language (SQL) • Microsoft Access user tools for generation SQL • Many DBMS have report generation capabilities for creating polished reports (Crystal Reports)6.32
  • 33. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Microsoft Access Data Dictionary FeaturesFigure 6-6Microsoft Access has arudimentary data dictionarycapability that displaysinformation about the size,format, and othercharacteristics of each fieldin a database. Displayedhere is the informationmaintained in the SUPPLIERtable. The small key icon tothe left of Supplier_Numberindicates that it is a key field.6.33
  • 34. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Example of an SQL Query Illustrated here are the SQL statements for a query to select suppliers for parts 137 or 150. They produce a list with the same results as Figure 6-5. Figure 6-76.34
  • 35. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management An Access Query Illustrated here is how the query in Figure 6-7 would be constructed using query-building tools in the Access Query Design View. It shows the tables, fields, and selection criteria used for the query. Figure 6-86.35
  • 36. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Designing Databases • Conceptual (logical) design: abstract model from business perspective • Physical design: How database is arranged on direct-access storage devices • Design process identifies • Relationships among data elements, redundant database elements • Most efficient way to group data elements to meet business requirements, needs of application programs • Normalization • Streamlining complex groupings of data to minimize redundant data elements and awkward many-to-many relationships6.36
  • 37. Normalization • The process of refining the data model built by the Entity-Relationship diagram. The Normalization technique, logically groups the data over a number of tables, which are independent and contain no duplicate data. The entities or tables resulting from normalization contain simple data items, with relationships being represented by replication of key data item(s).6.37 2-37
  • 38. Steps towards Normalization • 1. To convert The E-R Model into Tables/Relations. • 2. Examine the tables for redundancy and if necessary, change them to non redundant forms. • 3. This non-redundant model is then converted to a database definition, which achieve the objective of the Database Design Phase.6.38 2-38
  • 39. So Normalization is • Refinement of the E-R Model • Segregation of data over many entities or tables • Normalized model converted to physical database tables.6.39 2-39
  • 40. Need For Normalization • Improves database design • Ensures minimum redundancy of data • Reduces need to reorganize data when design is modified/enhanced • Removes anomalies for database activities6.40 2-40
  • 41. … • The tables derived from the E-R Models may be complex attributes, which have to be removed. The process of normalization also removes any undesirable consequences, resulting from database activities like inserting, updating and deleting values in a table.Storage space may also be conserved, thus resulting in a more efficient database.6.41 2-41
  • 42. Unnormalized Data Structure • Unnormalized data structure contains redundant and disorganized data, which needs to be organized, by dividing the data over several, tables to avoid redundancy. This is achieved by gong through the process of normalization. • Example……6.42 2-42
  • 43. Suppli Supplier Name Suppli City Part Part W Qty City Design er er Supplier Cod Name eig Code Status e ht SO1 RAM 15 CALCUTTA 101 SCRE 8 500 MUMBAI W SO2 SHYAM 20 CHENNAI 102 NUT 16 200 HYDERABA D SO3 AMIT 25 HYDERABA 103 BOLT 20 250 CHENNAI D SO4 RAJESH 15 MEMBAI 104 NUT 16 300 MUMBAI SO5 SUNDER 25 HYDERABA 105 BOLT 20 50 CALCUTTA D SO6 MURLIDHARAN 15 JAIPUR 106 NUT 16 200 CALCUTTA6.43 2-43
  • 44. The Above table presents several difficulties in operations like.. • Insertion of Fields: If a new field is introduced into the system, it cannot be added to the database, until it becomes related to another existing field, eg if a supplier name is introduced, its details cannot be entered in the table unless a part name is present for that supplier.6.44 2-44
  • 45. • Updation of Fields : If the supplier code of a supplier is to be modified , it has to be changed throughout the table, in all occurrences of the supplier record. Missing out even a single correction, would result in inaccurate data.6.45 2-45
  • 46. • Deletion of Fields : if information related to a specific column is to be deleted, the entire row has to be deleted, which results in loss of required information. For example, if the row of the supplier, ‘Amit’ is deleted, the information about the ‘Part Name’ is lost. Deletion of supplier details also deletes other details.6.46 2-46
  • 47. Relational Data Integrity • Candidate Key: Most of the relations have an attribute, which can uniquely identify each tuple in a the relation. In some .cases attribute is called the CANDIDATE KEY. Candidate Key: Is an attribute that can uniquely identify each tuple in the relation.6.47 2-47
  • 48. Steps in Normalization • First Normal Form (1NF) : Underline domain should have atomic values ie there should be no nested relations. • Identify repeating groups of fields • Remove repeating to a separate table • Identify the keys for the tables • Key of parent table is brought as part of the concatenated key of the second table.6.48 2-48
  • 49. Second Normal Form (2NF) • No subset of primary key should identify a record uniquely. • Check if all fields are dependent on the whole key. • Remove fields that depend on part of the key • Group partially dependent fields as a separate table. • Name the tables • Identify key(s) to the tables(s)6.49 2-49
  • 50. Third Normal Form (3NF) • All the non-key fields of the table are independent of all other non-key fields of the same table. There should be no transitive- dependency of non-key fields on other non-key fields. OR All the non-key attributes of the table are independent of all other non-key attributes of the same table. • Remove fields that – Depend on other non-key fields. – Can be calculated or derived from logic • Group interdependent fields as separate tables, identify the key and names the table6.50 2-50
  • 51. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management An Unnormalized Relation for Order An unnormalized relation contains repeating groups. For example, there can be many parts and suppliers for each order. There is only a one-to-one correspondence between Order_Number and Order_Date. Figure 6-96.51
  • 52. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Normalized Tables Created from Order After normalization, the original relation ORDER has been broken down into four smaller relations. The relation ORDER is left with only two attributes and the relation LINE_ITEM has a combined, or concatenated, key consisting of Order_Number and Part_Number. Figure 6-106.52
  • 53. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Entity-relationship diagram • Used by database designers to document the data model • Illustrates relationships between entities • Distributing databases: Storing database in more than one place • Partitioned: Separate locations store different parts of database • Replicated: Central database duplicated in entirety at different locations6.53
  • 54. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management An Entity-Relationship Diagram This diagram shows the relationships between the entities ORDER, LINE_ITEM, PART, and SUPPLIER that might be used to model the database in Figure 6-10. Figure 6-116.54
  • 55. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management • Distributing databases • Two main methods of distributing a database • Partitioned: Separate locations store different parts of database • Replicated: Central database duplicated in entirety at different locations • Advantages • Reduced vulnerability • Increased responsiveness • Drawbacks • Departures from using standard definitions • Security problems6.55
  • 56. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Distributed Databases There are alternative ways of distributing a database. The central database can be partitioned (a) so that each remote processor has the necessary data to serve its own local needs. The central database also can be replicated (b) at all remote locations. Figure 6-126.56
  • 57. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Very large databases and systems require special capabilities, tools • To analyze large quantities of data • To access data from multiple systems • Three key techniques • Data warehousing • Data mining • Tools for accessing internal databases through the Web6.57
  • 58. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Data warehouse: • Stores current and historical data from many core operational transaction systems • Consolidates and standardizes information for use across enterprise, but data cannot be altered • Data warehouse system will provide query, analysis, and reporting tools • Data marts: • Subset of data warehouse • Summarized or highly focused portion of firm’s data for use by specific population of users • Typically focuses on single subject or line of business6.58
  • 59. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making Components of a Data Warehouse The data warehouse extracts current and historical data from multiple operational systems inside the organization. These data are combined with data from external sources and reorganized into a central database designed for management reporting and analysis. The information directory provides users with information about the data available in the warehouse. Figure 6-136.59
  • 60. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making The IRS Uncovers Tax Fraud with a Data Warehouse • Read the Interactive Session: Organizations, and then discuss the following questions: • Why was it so difficult for the IRS to analyze the taxpayer data it had collected? • What kind of challenges did the IRS encounter when implementing its CDW? What management, organization, and technology issues had to be addressed? • How did the CDW improve decision making and operations at the IRS? Are there benefits to taxpayers? • Do you think data warehouses could be useful in other areas of the federal sector? Which ones? Why or why not?6.60
  • 61. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Business Intelligence: • Tools for consolidating, analyzing, and providing access to vast amounts of data to help users make better business decisions • E.g., Harrah’s Entertainment analyzes customers to develop gambling profiles and identify most profitable customers • Principle tools include: • Software for database query and reporting • Online analytical processing (OLAP) • Data mining6.61
  • 62. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making Business IntelligenceFigure 6-14A series of analytical toolsworks with data stored indatabases to find patternsand insights for helpingmanagers and employeesmake better decisions toimprove organizationalperformance.6.62
  • 63. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Online analytical processing (OLAP) • Supports multidimensional data analysis • Viewing data using multiple dimensions • Each aspect of information (product, pricing, cost, region, time period) is different dimension • E.g., how many washers sold in East in June compared with other regions? • OLAP enables rapid, online answers to ad hoc queries6.63
  • 64. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making Multidimensional Data ModelFigure 6-15The view that is showing isproduct versus region. Ifyou rotate the cube 90degrees, the face that willshow is product versusactual and projected sales. Ifyou rotate the cube 90degrees again, you will seeregion versus actual andprojected sales. Other viewsare possible.6.64
  • 65. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Data mining: • More discovery driven than OLAP • Finds hidden patterns, relationships in large databases and infers rules to predict future behavior • E.g., Finding patterns in customer data for one-to-one marketing campaigns or to identify profitable customers. • Types of information obtainable from data mining • Associations • Sequences • Classification • Clustering • Forecasting6.65
  • 66. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Predictive analysis • Uses data mining techniques, historical data, and assumptions about future conditions to predict outcomes of events • E.g., Probability a customer will respond to an offer or purchase a specific product • Text mining • Extracts key elements from large unstructured data sets (e.g., stored e-mails)6.66
  • 67. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Web mining • Discovery and analysis of useful patterns and information from WWW • E.g., to understand customer behavior, evaluate effectiveness of Web site, etc. • Techniques • Web content mining • Knowledge extracted from content of Web pages • Web structure mining • E.g., links to and from Web page • Web usage mining • User interaction data recorded by Web server6.67
  • 68. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making • Databases and the Web • Many companies use Web to make some internal databases available to customers or partners • Typical configuration includes: • Web server • Application server/middleware/CGI scripts • Database server (hosting DBM) • Advantages of using Web for database access: • Ease of use of browser software • Web interface requires few or no changes to database • Inexpensive to add Web interface to system6.68
  • 69. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making Linking Internal Databases to the Web Users access an organization’s internal database through the Web using their desktop PCs and Web browser software. Figure 6-166.69
  • 70. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Managing Data Resources The Databases Behind MySpace • Read the Interactive Session: Technology, and then discuss the following questions: • What kind of databases and database servers does MySpace use? • Why is database technology so important for a business such as MySpace? • How effectively does MySpace organize and store the data on its site? • What data management problems have arisen? How has MySpace solved or attempted to solve these problems?6.70
  • 71. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Managing Data Resources • Establishing an information policy • Firm’s rules, procedures, roles for sharing, managing, standardizing data • E.g., What employees are responsible for updating sensitive employee information • Data administration: Firm function responsible for specific policies and procedures to manage data • Data governance: Policies and processes for managing availability, usability, integrity, and security of enterprise data, especially as it relates to government regulations • Database administration : Defining, organizing, implementing, maintaining database; performed by database design and management group6.71
  • 72. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Managing Data Resources • Ensuring data quality • More than 25% of critical data in Fortune 1000 company databases are inaccurate or incomplete • Most data quality problems stem from faulty input • Before new database in place, need to: • Identify and correct faulty data • Establish better routines for editing data once database in operation6.72
  • 73. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Managing Data Resources • Data quality audit: • Structured survey of the accuracy and level of completeness of the data in an information system • Survey samples from data files, or • Survey end users for perceptions of quality • Data cleansing • Software to detect and correct data that are incorrect, incomplete, improperly formatted, or redundant • Enforces consistency among different sets of data from separate information systems6.73

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