Tacit knowledge unstructured knowledge residing

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Tacit knowledge (unstructured): knowledge residing ( 存在于 ) in heads of employees, rarely written down 5.2 The way to manage these three kinds of knowledge: 针对三种知识的 管理方式 : For unstructured tacit knowledge, using collaboration tools and learning management systems to share and codify them . Collaboration tools: Social bookmarking ( 社会书签 ) : allow users to save their bookmarks publicly and tag with keywords. Learning management systems (LMS): Provide tools for management, delivery, tracking and assessment of various types of employee learning and training. For semi-structured and structured knowledge, using document management systems and database management systems ( 文件管理系 统和数据库管理系统 ) to collect, store, distribute and apply. 6. Business intelligence : 6.1 Definition BI is tools for consolidating ( 整 合 ), analysing and providing access to large amounts of data to improve decision making 6.2 How do Business Intelligence work? A series of analytical tools works with data stored in databases to find patterns and insights for helping managers and employees make better decisions to improve organizational performance. 一系列分析工具可以处理存储在 数据库中的数据,以便找到模式和见解,帮助管理人员和员工做出更好的决策以改善组织 绩效。 6.3 Techniques are used in BI: 1. Software for database reporting and querying ( 查询 ) 2. Tools for multidimensional data analysis 多 维 数 据 分 析 工 具 (online analytical processing) 3. Data mining 数据挖掘 4. Big data
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6.4. Artificial intelligence (AI) becomes a necessity Businesses absolutely need to adopt AI in order to stay relevant. Voice-activated home assistants, smartphones, Big Data, and Insight- as-a-Service vendors will all have big years as a result of this AI adoption. But the biggest winners this year are data scientists and Chief Data Officers (CDO) who will be in high demand for a long time. Forrester predicts that AI will blur the boundaries between structured and unstructured data, and 50% of CDO’s will start to report directly to the CEO. As a result, over 13% of data-related jobs on Indeed.com are for data engineers, compared to 1% for data scientists. This reflects the need for practical, action-oriented data pros that can directly impact the bottom line. 6.5. Primary activities in the BI process Data acquisition: the process of obtaining, cleaning, organizing, relating and cataloguing data source. BI Analysis: the process of creating business intelligence. The four fundamental categories are reporting, data mining, Big Data, and knowledge management. Publish results: the process of delivering business intelligence to the knowledge workers who need it. Push publishing delivers business intelligence to users without any request from the users. Pull publishing requires the user to request BI results.
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6.6. Online Analytical Processing (OLAP) It supports multidimensional data analysis and enables users
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