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NIH See Not-Invented-here. Nohria, Nitin
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- Nonaka, Ikujiro
- Not-Invented-Here (NIH)
- Object Oriented Databases (OODBs)
- OLAP See Online Analytical Processing. Online Analytical Processing (OLAP)
- Ontology
- OODBs
NIHSee Not-Invented-here. Nohria, NitinA well known professor at the Harvard Business School, Nohria’s research centers on leadership, corporate accountability, and organizational change. His book, Building the Information Age Organization, examines the role of information technology in transforming organizations. In Networks and Organizations: Structure, Form, and Action, an edited volume of original articles, he explores the emergence of network-like organizations. He is the author of over 75 journal articles, book chapters, cases, working papers, and notes. His article “What’s Your Strategy for Managing Knowledge?” Harvard Business Review 77, No. 2 (March-April 1999): pp. 106-116. co-written with Morten Hansen and Thomas Tierney is a highly influential piece that explains how companies can strike a balance between information technology and human intervention while managing knowledge. Nonaka, IkujiroOne of the leading knowledge management gurus in the world, Ikujiro Nonaka is a Professor at the Haas School of Business at the University of California, Berkeley and the Founding Dean of the Graduate School of Knowledge Science at the Japan Advanced Institute of Science and Technology (JAIST). He has authored or coauthored several books, including the widely acclaimed, The Knowledge-Creating Company and has written several articles in various international academic and managerial journals. He has also been the editor of several international journals and conducted international knowledge management seminars for managers. Not-Invented-Here (NIH)Individuals, departments and organizations often have a mental block about using an idea / technology developed by an outsider. NIH is a major barrier to organizational learning. Companies have tried to deal with this syndrome in various ways such as by introducing “Steal Shamelessly” awards. O
The type of database application should dictate the choice of database management technology, namely Relational databases and Object Oriented Databases. In general, database applications can be categorized into data collection and information analysis: Data collection applications focus on entering data into a database and providing queries to obtain information about the data. These applications contain relatively simple data relationships and schema design. So, relational database management systems (RDBMs) are better suited for these applications. Examples are accounts payable, accounts receivable, order processing, and inventory control. Information analysis applications involve navigation through and analysis of large volumes of data. Object oriented databases (OODBs) are better suited for such applications. OODBs are also used in applications handling BLOBs (binary large objects) such as images, sound, video, and unformatted text. OODBs support diverse data types rather than only the simple tables, columns and rows of relational databases. Examples of these applications are CAD / CAM / CAE, production planning, network planning, and financial engineering. OODBS facilitate the unification of the application and database development into a seamless data model and language environment. As a result, applications require less code and use more natural data modeling. So code bases are easier to maintain. Object developers can write complete database applications with a modest amount of additional effort. In contrast to a relational DBMS where a complex data structure must be flattened out to fit into tables or joined together from those tables to form the in-memory structure, OODBs do not store or retrieve a web or hierarchy of interrelated objects. The one-to-one mapping of object programming language objects to database objects provides higher performance management of objects. It also enables better management of the complex interrelationships between objects. So OODBs are better suited for applications such as financial portfolio risk analysis systems, telecommunications service applications, world wide web document structures, design and manufacturing systems, and hospital patient record systems, which have complex relationships between data. OLAPSee Online Analytical Processing. Online Analytical Processing (OLAP)OLAP is part of the broader category of software applications which go by the name of business intelligence. The typical applications of OLAP are in business reporting for sales, marketing, management reporting, business performance management, budgeting and forecasting, financial reporting and similar areas. OLAP is a slight modification of the traditional OLTP (Online Transaction Processing). OLAP databases are capable of handling queries which are more complex than those handled by standard relational databases through the ability to view data by different criteria, advanced calculation capability and specialized indexing techniques OntologyRefers to the levels of knowledge creation. At the lowest level, we have the individual, then we have the organization and finally we have more than one organization. In a strict sense, knowledge is created only by individuals. The organization can provide the context and the necessary support but it is individuals who create knowledge. Knowledge management is all about amplifying this knowledge and crystallizing it as part of the knowledge network of the organization. From the individual level, the process moves to intra organizational and inter organizational levels. OODBsSee Object oriented databases. Organizational Knowledge AwarenessAwareness of both the existing knowledge and the knowledge gaps which exist. Such knowledge is the starting point in knowledge management. Knowledge awareness can be analyzed in various ways. Elias Carayannis has identified four states of knowledge awareness as deputed in the matrix below:
Similarly, Michael Earl has also developed a 2 x 2 Matrix as depicted below:
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