Organizational learning at Telstra attempts to highlight the competitive advantage by improving or learning faster and creating new knowledge. The interest in knowledge management is being driven in part by speed of connectivity, increasing the knowledge content of products and services, shorter development cycles of new products and services, the overload of information as prolific generation of knowledge. It also involves the requests by individuals to rely on the experience of people across the organization. Since its adoption by the business community and the public, the Internet has led to an increase in creative collaboration, the learning and research, electronic commerce, and immediate information. With improved technology, gone are the days of dusty shelves, imperfect or distorted messages and slow mail. In many respects, the practice of organizational learning will continue to evolve with the growth of collaboration applications available from the information technology and Internet (Dimovski, 1998). The electronic learning (e-learning), online discussions, and software are examples of collaborative uses of knowledge management that support the process. Each use may increase the level of research available to an employee, while providing a platform to achieve goals or actions. The data mining is the practice (by automatic or semiautomatic means) to seek and explore stored data resulting in the discovery of meaningful patterns and rules (Wiig, 1997). To do this, Telstra uses computational techniques from statistics, the automation of knowledge and pattern recognition.
Telstra试图突出的竞争优势，提高学习速度和创造新知识的组织学习。知识管理中的利益被驱动部分由高速连接，提高产品和服务的知识含量，缩短开发周期的新产品和服务，信息过载和知识丰富的代。它还包括要求个人依靠跨组织的人的经验。由于其采用的商业界和公众，互联网已经导致创造性合作的增加，电子商务的学习和研究，，和即时的信息。随着技术的进步，已经是灰尘的书架上的天，不完全的或扭曲的消息和缓慢的邮件。在许多方面，组织学习的实践将继续与协作应用程序可从信息技术和互联网的发展演变（DIMOVSKI，1998）。电子学习（电子学习），在线讨论，和软件的协同知识管理支持流程使用。每次使用可以提高研究水平的一个雇员，而要达到的目标或行动提供一个平台。数据挖掘是实践（自动或半自动方法）寻求和探索的存储数据的产生有意义的模式和规则发现（是的，1997）。为此，澳洲电信应用计算机技术统计，知识和模式识别的自动化。
