Ch4_9a_SN_F09

Ch4_9a_SN_F09 - 1 Data and Knowledge Management [Chs. 4; 9]...

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1 Data and Knowledge Management [Chs. 4; 9] Learning Objectives: Data Management: Critical for computing Data Warehousing for decision support I f ti d k l d di Information and knowledge discovery Data mining: Concepts and Applications; benefits Data presentation & visualization for decision support Web-based data management Types of knowledge and knowledge management Observations IE332 F’09 Observations: 1. Data, data, knowledge, knowledge, … a funny resource: The more you use, the more you create! (compare to other resources?) 2. Even if we had all the data and knowledge, does it assure good decisions? Why? If we have all the models and no data / knowledge? 3. One datum, several data, therefore, “data are collected” 2 4.1 Data Management Critical for computing: IT applications cannot work without data. Can optimization models work w/o it? Data must be high-quality: (1) accurate, (2) complete, (3) timely, (4) consistent, (5) accessible, (6) relevant, and (7) concise -- The 7 key attributes . What about security? Difficulties of managing Data: • The amount of data increases exponentially with time WHY? • Data are scattered throughout the organization • Data are collected by many individuals IE332 F’09 • Data gathered using several methods and devices • Better organizational decision-making requires considering large amount of external data • Data security, quality , and integrity are critical, yet are a challenge
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3 Data Life Cycle (Fig. 4.1) IE332 F’09 4 Data Sources – where data are created Internal Data Sources: data about people, products, services, and processes Examples Examples: Personal Data: IS users and other employees can document their own expertise by creating personal data Examples: External Data Sources: Data from commercial databases, from sensors, images, and satellites Examples of external data sources: IE332 F’09 Examples: Surgery Center; Universities; Courts; Mfg. & Supply enterprises; Insurance Agencies; Banks; Sensor Networks; Social Networks
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5 Document Management Automated control of electronic documents, page images, spreadsheets, word processing documents, through their entire life cycle within the organization The major tools of document management are workflow software, authoring tools, scanners, imaging systems, and database Document Management Systems (DMSs): Computer systems that identify store, retrieve, track, and present information in an electronic format to decision makers IE332 F’09 makers Leading DBMS companies today: ORACLE; CA with Ingres; IBM with DB/2; Informix; Microsoft with Access and SQL Server 6 Data Warehousing Transaction Processing: The data are organized in hierarchical structure and centrally processed Analytical Processing Analysis of accumulated data Analytical Processing: Analysis of accumulated data Data Warehouse: A repository of subject-oriented historical data that are organized to be accessible in a form readily acceptable for analytical processing Summary of strategic applications of data warehousing in different industries – see Sec. 7.4 and Table 7-1
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This note was uploaded on 01/19/2012 for the course IE 230 taught by Professor Xangi during the Spring '08 term at Purdue.

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Ch4_9a_SN_F09 - 1 Data and Knowledge Management [Chs. 4; 9]...

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