Lecture 12 Flashcards
data
A collection of raw symbols, numbers, words, images or sounds without specific meaning. It represent facts, recorded by observation or research.
information
Data that is processed and given context, making it meaningful and useful.
knowledge
The result of processing information combined with skills, experience, and judgment.
knowledge management
How organizations collect, organize, share, and use knowledge effectively.
Processes of knowledge management
- Acquiring Knowledge: Gather information internally and externally, then process it to make informed decisions.
- Accessing Knowledge: Identify who holds knowledge and where it is stored.
- Sharing Knowledge: Enable knowledge exchange between people or teams
- Applying Knowledge: Individuals have to use knowledge effectively to make decisions or solve problems.
- Evaluating Knowledge: Assess whether the knowledge is necessary or relevant to avoid information overload.
Two views on knowledge management
- objectivist perspective (explicit knowledge)
- subjective perspective (tacit knowledge)
objectivist perspective (explicit knowledge)
- Focuses on knowledge as facts and information that can be stored (e.g., databases, manuals).
- Uses traditional IT tools like ERP systems.
- Explicit knowledge: Easily documented and shared
subjective perspective (tacit knowledge)
- Focuses on knowledge gained through practice, experience, and social interaction.
- Uses collaborative tools like wikis or Teams to share and develop knowledge.
- Implicit knowledge: Learned through experience or practice, not easily written down.
Implicit knowledge
knowledge that is learned through experience or practice, not easily written down.
Explicit knowledge
knowledge that is easily documented and shared
Socialization
tacit > tacit
Sharing tacit knowledge through social interaction, such as mentoring, storytelling, or observing experts.
Externalization
tacit > explicit
Converting tacit knowledge into explicit formats through documentation or discussion.
Combination
explicit > explicit
Combining existing explicit knowledge (e.g., reports, data, or documents) to create new, improved explicit knowledge.
Internalization
explicit > implicit
Learning explicit (e.g., written) knowledge and making it part of your own understanding to create new ideas.
business intelligence
Skills, processes, technologies, applications and practices used to support decision making
= IS
It transforms raw data into actionable insights to improve performance, seize (grijp) opportunities, and solve problems.
BI system
knowlege management applications that help people make decisions
= executive information system
= decision support system
operational vs. strategic BI use
Operational BI:
* Purpose: Supports daily activities and processes.
* Focus: Short-term, real-time insights into performance.
* Example: Monitoring daily sales or stock levels.
Strategic BI:
* Purpose: Helps with long-term decisions and strategic planning.
* Focus: Long-term, analyzing trends and making predictions.
* Example: Deciding which products to allocate more marketing budget based on multi-year sales data.
Operational BI focuses on the present, while Strategic BI supports future decision-making.
RFM
giving each customer a score from 1-10 on recency (how recent was last purchase), frequency (how often) and monetary value (how much spend)
Reporting BI vs. Data mining BI
Reporting BI
- Collects, sorts, filters and visualizes/reports data, but provides no insights.
- Interpretation is up to analyst.
Data mining BI
- Finds patterns and relationships among data for classification and prediction
- Exploratory data mining (unsupervised) = Looking for patterns in data, but no statistical testing.
- Confirmative data mining (supervised) = Testing hypothesis
exploratory data mining
looking for patterns in data but no testing
confirmative data mining
testing expectations
