1	Managing Information Resources Chapter 7 Information Systems Management In Practice 5E McNurlin & Sprague
2	Introduction Data vs. Information vs. Knowledge Data: facts Information: data in context Knowledge: information with direction or intent - it facilitates a decision or action Companies’ greatest asset: the knowledge “embedded” in employees’ heads (tacit knowledge)
3	Managing Corporate Records: The Problem: Inconsistent Data Definitions Problem: data definitions incompatible from application to application, from department to department, from site to site, and from division to division Reason: to get application systems up and running quickly, system designers sought data from the cheapest source or politically expedient source Result: different files with different names for same data and same name for different data
4	Managing Corporate Records: The Problem: Inconsistent Data Definitions In order to get corporate data under control, use of DBMS - database management software A “database administrator” to manage DBMS to improve the problem of inconsistent and redundant data Broader definition of the data administration role - Standard format for data crossing organization boundaries Effective use of data dictionaries to control standard data definitions
5	The Four Roles of Data Administrators Clean up data definitions: getting rid of data redundancies and inconsistencies, e.g., two names for same data item, design integrity flags, and train users on meaning of data Control shared data - data used by two or more units - and analyze impact of changes to programs that use shared data; data dictionaries provides one place to look for all uses of data.
6	The Four Roles of Data Administrators Manage distributed data - geographically dispersed - it also may cross hierarchical levels of the organization Maintain data quality: involves the design and implementation of procedures to maintain quality of data, usually owners of data edit and verify the accuracy, defining who owns the data
7	The Importance of Data Dictionaries Systems and procedures for storing and handling an organization’s data definitions Purpose: eliminate errors of understanding, ambiguities, and difficulties in interpreting data Ideal sequence: Set up the data administration function Develop data standards Purchase and install a DBMS Install the data dictionary as the first dB application
8	Case Example: Monsanto International, decentralized. Vision: responsive to customer needs thinking and acting from global perspective taking risks to enter new markets treating earth as a closed system -consumption and contamination cannot be sustained creating a thriving environment for employees
9	Monsanto (cont.) Three enterprise-wide IT projects: Financial Transaction System: SAP - covers all core business transactions, including finance, order processing, inventory management, product planning, and manufacturing resource planning. Knowledge Management Architecture: Data warehouses that can be sliced and diced with drill-down capability; compare and leverage information. Enterprise Reference Data: SAP repository of master table information in the company. Includes vendors, customers, suppliers, etc. with different views for purchasing, accounting, etc. Enables integration.
10	Monsanto (cont.) Getting the data into shape - ERD Stewardship Dept. Set data standards and enforce quality Entity specialists, key managers. with the greatest stake in the quality of data Analysts who manage the data - a global resource that the entire company uses
11	Managing Data: The Three-Level Database Model See Figure 7-4 Level 1 - The external, conceptual, or local level, containing the various “user views” of the corporate data that each application program uses Level 2 - The logical or “enterprise data” level, encompassing all an organization’s relevant data, under the control of the data administration. Level 3 - The physical or storage level, specifying the way the data is physically stored
12	The Three-Level Database Model: Advantages Logical data can be separated from the method of physical storage, different physical devices can be used without changing application programs. Logical data relationships can vary from different programs that use the data, without requiring data redundancy. Applications can use a subset of the DB and organize it, again without redundancy, in the best manner for the application.
13	Four Data Models Hierarchical model: structures data so that each element is subordinate to another in a strict hierarchical manner, like boxes in organization chart Network model: allows each data item to have more than one parent, relationships stated by pointers
14	"Relational DBMS:" Relational DBMS: where the relationships among data items are not expressly stated by pointers. Instead it is up to the DBMS to find the related items, based on the values of specified data fields. Store data in tables, each row=tuple, col.=attributive entity, DB of choice today. See Figure 7-5 for relational operations
15	"Designed to widen the use..." Designed to widen the use of DB to new kinds of applications: CAD, medical applications, knowledge representation for AI. Retains traditional DBMS features and add two new concepts. Object management: The mgt. of complex kinds of data, e.g., multimedia and procedures Knowledge Management: the management of large numbers of complex rules for reasoning Objects can be of any type: e.g., spreadsheet, video clip, photograph. A collection of objects is an object-base or object-oriented database.
16	A Look to the Future NASA needs to store 10¹⁶ bytes of satellite images, enough to fill 10K optical disk jukeboxes CAD data for a skyscraper DNA sequence of human genome, several billion elements long for genetic make-up research Customer buying patters at large retail chains - data mining Multimedia DB of insurance policies Design databases should notify designers when another designer has made a modification to the system Need new data models to handle spatial data, time, and uncertainty
17	A Look to the Future A single worldwide file system (?) Distributed heterogeneous DB - for inter-company DB Security - authenticating enquirers
18	Distributing Data Distributed databases - 12 rules for a distributed database, see Figure 7-6. Operating principles depend on underlying DB being relational. SQL - Standard Query Language - a standard language for accessing relational DB. A data definition language for creating relational tables, indexes to data, and fields of data A data manipulation language for entering information into a DB A data control language for handling security functions
19	Alternatives to “True” Distributed Databases Downloaded data files: e.g., sending data from mainframes to PCs, most popular method for distributing data Copies of data stored at nodes: helps process customer activity during the day, night official updating of the master files Not fully synchronized DB: second copies in cache, errors cause a new primary copy
20	Alternatives to “True” Distributed Databases Server-based DB: In a distributed DB, each node has a copy of the DBMS and dictionary. In server DB, applications must know where data is located; does not support location transparency. Appropriate for higher-performance transaction processing. Federated databases: Existing DB defined independently and retain rules for others to access its data. Works when incompatible DB (text, alphanumeric, and image) are needed in a single application.
21	Managing Information: Issues Value Issues: Information’s value depends on the recipient and the context. The only practical way to establish the value of information is to put a price on it, and see if anyone buys. Tools: Information maps: Point to the location of information, e.g., where to get quick answers to questions Information guides: People who know where information can be found. Business documents: Provide organization and context - what documents an organization needs Groupware: People to share information across distances
22	Managing Information: Issues Usage Issues: Deals with how people use information Information’s complexity needs to be preserved - information should not be simplified to be made to fit into a computer, because this truncates sharing and conversations. People do not easily share information, even though its value grows as it is shared. Culture often blocks sharing. Technology does not change culture.
23	Managing Information: Issues Sharing Issues: A sharing culture must be in place or the existing disincentives will thwart the use of sharing systems. Information architectures have failed because they do not take into account how people use the information. Sharing of corporate performance figures is beneficial, but sharing of rumors can be de-moralizing. Separating information from non-information is an information management issue. Getting value out of information requires more than a technology.
24	Four Types of Information Fig. 7.2 presents a matrix representative of these four types of information. Internal/record-based has been the focus of attention of information systems, the type of information computer-based applications generate and manage easily. External/record-based: can be accessed over the Internet via public DBs. Internal/document-based: intranet document management 95% of the information. In most organizations it is in document form, 5% data. External/document-based: WWW
25	Four Types of Information Figure 7-8 lists the four categories of information and shows typical corporate authority, sources of information, and examples of technologies used in managing each: Internal record-based Internal document-based External record-based External document-based
26	Toward Managing Knowledge The more people are connected, and the more they exchange ideas, the more their knowledge spreads and can thus be leveraged. Process is the key - how do we transfer tacit knowledge? IT is an enabler.
27	Conclusion The job of the IS department is widening: get data into shape create and build an infrastructure for managing the full range of information types helping the firm leverage the tacit knowledge of its employees Companies that address all three areas, and start implementing IT-based programs in all three, will have a significant edge over their competitors because they will be able to leverage their intellectual assets.