Figure 7-2: four types of information: internal Document- based Record-based external Structure of information Source of information internal
Internal changes Allows companies to bring internal data and information together from far-flung files and databases and makes them available company-wide. Gives employees access to far more corporate data and information than they ever had before. The ability to handle and transmit media increases the variety of information formats and content.
External Changes The availability of external data has exploded with the internet. The inherent structure of the information resources that need to be managed has broaden considerably: Data warehouses store large amounts of data to be analyzed with data mining techniques to support decision making for applications such as CRM. Less structured concept-based information is becoming dominant. Knowledge Management is becoming a key to exploiting the intellectual assets of an organization.
Structure of Information Record-based contains primary facts about entities such as individual employees, customers, parts, or transactions. Well structured data records are used for holding a set of attributes that describe each entity. Document-based information pertains primarily to concepts, ideas, thoughts and opinions. Less structured documents or messages with a variety of forms.
Figure 7.1: Difference in Structure: Data RecordsDocuments Item of Interestentityconcept or idea Attribute of Itemfieldset of symbols All attributes of Item records recordlogical paragraph All related Itemsfiledocument A Group of Related Filesdatabasefile cabinet A Collection of Databasesapplication-library, record center system “Data Model”hierarchical, relational (representational approaches)
Figure 7-2: four types of information: Traditional EDP/MIS Public databases Word processing management Corporate library web sites Record- based Document -based externalinternal Structure of information Source of information
Managing Corporate Data Records Dirty Data Database Management Systems Data Administration
Management Corporate Data Records The Problem: Inconsistent Data Definitions Incompatible data definitions Why is this hard for management? What if IT department were managing data?
Management Corporate Data Records The Role of Data Administration Clean Up Data Definitions Control Shared Data Manage Data Distribution Maintain Data Quality
Management Corporate Data Records The Importance of Data Dictionaries Main purpose of data dictionaries When should data dictionaries be considered?
Managing Information Information – intermediary for action Info Managing issues Value issues Usage issues Sharing issues
Value Issues Information’s value is contextual Tools used to increase value of info by firms Information maps Information guides Business documents Groupware
Usage Issues Information is inherently messy and therefore its complexity needs to be preserved It is not easily shared Organizational culture blocks sharing Technology does not change culture
Sharing Issues A sharing culture must be in place Technical solutions do not address the sharing issue Info architecture have failed because they do not take into account how people actually use the information Working out info issues requires addressing entrenched attitudes about organizational control
Sharing Issues (cont’d) Sharing information is not good in all cases Limits are necessary Hiring practices play a role Sharing ideas needs to be rewarded (e.g. promotion) for a sharing environment to exist
Managing Data Four Data Models Three Levels of Managing Data Distributing Data Twelve Rules for Distributing Data Data Warehouse
Managing Data Logical or enterprise data: DBMS Level 1: Level 2: Level 3: External, conceptual, local level, user view Physical or storage level, data records
Four Data Models Hierarchical: Parent/Child Relationship Network: each data item more than one parent Relational: create relationships on the fly Object: Data, methods, and attributes
Distributing Data Data definition language: creating tables, creating indexes to data, and defining fields of data Data manipulation language: for entering data into a database and accessing and formatting the data Standard Query Language: SQL Data control language: for handling security functions
12 Rules for Distributed Database Local autonomy No reliance on central site Continuous Operation Location independence Fragmentation independence Replication independence Distributed Query Distributed Transaction Hardware independence OS independence Network independence Database independence
Data Warehouse Database that contains data from many sources, including operational sources. Repository of Metadata Data is “cleaned” and formatted to a common structure OLAP: Online Analytical Processing
Figure 7.9: Information Management is different from Knowledge Management. Information Management: 1)Emphasizes delivery and accessibility of content. 2)Has heavy technology focus. 3)Assumes information capture can be standardized and automated. Knowledge Management: 1)Emphasizes added value to content by filtering, synthesizing, interpreting, and adding context. 2)Balances focus between technology and culture or work practice. 3)Requires ongoing human input and links to communication.
The term management brings to mind having control over something, and knowledge cannot be control. It can only be leveraged through process and culture. The more people are connected and exchange ideas, the more knowledge can spread and be leveraged. Many feel that the term “ Knowledge Management” creates the wrong impression.
Several companies have stopped using the term Knowledge Management and replaced it with the term Knowledge Sharing.