Summary
Knowledge Management is a concept used in companies, which aim to transfer existing knowledge and experience to employees, so that it can be used as a resource available to others in the organization. Most of the Organizations that have already developed their first Knowledge Management Systems, have taken into account the need to have the computerized support of a General Information Store that is called in Anglo-Saxon terms "DATA WAREHOUSE", or at least one Warehouse of Partial and Summarized Information on an area of critical knowledge for the Organization, such as: Commercial, Product, Marketing, etc. Information.
Currently, more and more information is being encoded in digital format, so that it is accessible by computer. Likewise, tools are being developed that allow searching effectively in databases, files, 'web pages, data warehouse, repositories, etc., and in this way extract information of added value, capture its meaning, organize it and make it available.
Knowledge Management and its link to Data Warehouses
The man and the knowledge that he possesses and contributes to the organization is the most important value that the entity has. This precept is recognized and used by the new management approach which is Knowledge Management, whose effective management technique involves acquiring, using and improving the knowledge necessary for the organization, creating an environment that allows it to be shared and transferred among all workers and cadres. address for them to use instead of rediscovering them.
Knowledge management is now considered to have ceased to be an assumption to become an effective management technique.
Definition of knowledge
Knowledge is the subject of study from different disciplines, such as philosophy, psychology, business management and, more recently, computer science, which is why there are different definitions according to the point of view and interest of those who speak. Although for the purposes of this work, the most pragmatic definitions from a business perspective are of interest, it is useful to know, for the sake of a better understanding and more effective collaboration with people interested in the other disciplines, various definitions as well as the terminology that surrounds the concept of knowledge..
Knowledge is a set of data on facts, truths or information stored through experience or learning (a posteriori), or through introspection (a priori). Knowledge is an appreciation of the possession of multiple interrelated data that alone have less qualitative value.
Knowledge begins with the senses, passes from these to understanding, and ends with reason. Just as in the case of understanding, there is a merely formal use of it, that is, a logical use since reason makes abstraction of all content, but there is also a real use.
Science obtains knowledge by following a method called the scientific method or experimental method, and the knowledge thus obtained is called scientific knowledge.
Types of knowledge
Of the many classifications that can be found for the purposes of this work, the one that divides knowledge into: tacit and explicit is interesting.
Tacit knowledge. This type of knowledge is the one that is not registered by any means and that is only obtained by acquiring knowledge in a practical way and it is only possible to transmit and receive it by consulting directly and specifically with the holder of this knowledge.
Explicit knowledge: This is knowledge based on concrete data with which your knowledge would be sufficient to take advantage of it without the need for any interpretation, expressing it in a simple way is “the theory”.
It is now up to us to ask what is the main difficulty when it comes to dealing with the knowledge management of a company. The raw material from which we start is information, in this case, our raw material is not scarce, rather the opposite, it is excessive. The information comes from various environments, clients, staff, institutions, etc…. We must eliminate redundant information and draw conclusions from relevant information. These analysis techniques are, among others, Data Mining and Data Warehouse.
- Data Mining: Set of techniques used for the process of capturing and analyzing the information available in the organization's repository or, even better, in the Data Warehousing repository. It uses database exploration techniques, allows the statistical treatment of the data and includes, in most cases, various formats for the output of the conclusions. Data Warehousing: Organized warehouse of all the information available to the company. This organization allows the analysis and access to information from the different areas of a business activity (sales, production, finance).
Evolution of Organizations towards Knowledge Management
Knowledge Management -GC- in a broad sense requires multiple actions in the organizations that wish to carry it out, and that affect the organization itself, the people that make it up and the computer resources used. In relation to the latter, the Data Warehouse constitutes an essential part thereof.
A Data Warehouse development project is, above all and above all a project - GC - and will require that in the company or organization that is carried out:
Evolve your business culture to make it possible.
Have suitably prepared human teams to develop you.
Use a development methodology that facilitates project management and control.
Have or acquire computer tools that allow both its analysis and design and its further development and commissioning.
To successfully carry out a QA project or a Data Warehouse project, there needs to be an appropriate balance between "human team" and "technology". Today, unfortunately, not all companies are in this situation, as evidenced by a study carried out in 1996 by the American Productivity and Quality Center organization, which found that "85% of companies have limitations in Knowledge Management".
A high percentage of Data Warehouse projects have not reached their planned objectives, and some were canceled before completion. The following point describes the most frequent barriers that affect KM projects. These barriers can take on even greater weight if, in addition, the development of the project is carried out without using a development methodology contrasted with its adaptation to these specific projects.
The first starting point that must be considered is the Data Warehouse Vision itself and the development alternatives.
A Data Warehouse must be seen as much more than a corporate data file that is critical to successfully executing company initiatives:
- It is also an encyclopedia specialized in topics that affect the company's work. It incorporates tools that allow managers, at all levels of the organization, the information they need. Not precisely "complex queries", but the relevant information requested, making it available to you reliably and quickly. It has great analogies to a physical warehouse, hence its name: Operational systems are what create the "data elements" that will be loaded into the Data Warehouse. Some of these data elements are summarized and summarized as "data components". Users of the Data Warehouse make their requests, which are delivered to them as "information products", these products are created from the "elements" and "components" that exist in the Data Warehouse.
The data warehouse, as a support for knowledge management
Most of the Organizations that have already developed their first Knowledge Management Systems, as we have commented in the previous report dedicated to these new systems, have taken into account the need to have the computer support of a General Information Warehouse that we called Anglo-Saxon terms «data warehouse», or at least a Partial and Summarized Information Store on an area of critical knowledge for the Organization, such as:
Commercial,
Product,
Marketing, etc. Information.
That in Anglo-Saxon terms we call "data mart".
In the proposed Development Methodology, we comment on the advisability of «establishing phases in the development of Data Warehouse projects». The first project should allow us to create the general structure of the Data Warehouse of our Organization and the first fully operational Data Mark from which we can extract knowledge that can be applied immediately to the business.
Subsequently, the general and long-range project of our Data Warehouse will be developed in successive phases, progressively building new Data Marts, whose summarized or summarized data will be extracted from the developing Data Warehouse.
In this way we achieve the fundamental objectives:
Have a General Information Store for the entire Organization. (the Company's Data Warehouse).
To have Critical Knowledge for the Business, according to the own priorities of each organization (using progressively created Data Marts, and the most suitable automatic knowledge obtaining tools).
To successfully undertake these projects, it is practically essential to use CASE tools that facilitate analysis and design, working with the company's information systems methodologies such as those presented.
Bibliography
1. CUESTA, Armando Santos, “Management of competences”, Ed. Academia, 2001.
2. GARCÍA, Gerardo Cabrera, “From the information age to the knowledge society”, Science, Innovation and Development Magazine, Vol. 6, No.4, 2001, p. 17-20.
3. Blanco, José M. “Knowledge Management, what for?”. 2001, available at www.gestiondelconocimiento.com
4. Editors of the virtual magazine Management for Success, “Guide for the implementation of Knowledge Management”, 2002, available at http:: //www.yesmfs.com
