- Identification of data
- Preprocessing
- Transformation to common format
- Data mining through algorithms
- Evaluation
Showing posts with label Data mining. Show all posts
Showing posts with label Data mining. Show all posts
Friday, September 18, 2009
Knowledge Discovery in Databases
Data mining used to find patterns in data
Labels:
Business analytics,
Data mining,
Knowledge Discovery,
Lesson 3
Tools and Techniques
Data mining
- Statistical methods
- Decision trees
- Case based reasoning
- Neural computing
- Intelligent agents
- Genetic algorithms
- Hidden content
- Group by themes
- Determine relationships
Data Mining
- Organizes and employs information and knowledge from databases
- Statistical, mathematical, artificial intelligence, and machine-learning techniques
- Automatic and fast
- Tools look for patterns
- Simple models
- Intermediate models
- Complex Models
Labels:
AI,
Business analytics,
Data mining,
Lesson 3,
machine-learning,
mathematical,
statistical
Tuesday, September 15, 2009
Business Intelligence: pg 24
BI is an umbrella term that combines architectures, tools, databases, analytical tools, applications and methodologies.
Its major objective is to enable interactive access (sometimes in real time) to data, to enable manipulation of data, and to give business managers and analysts the ability to conduct appropriate analysis.
By analysing current, historical data and situations, performance - decisionmakers get valuable insight that enable them to make more informed and better decisions.
The process of BI is transformation of data to inormation, then to decisions and finally to actions.
4 major components:
Data warehouse
Conerstone of any medium to large BI system. Includes current and historical data.
Business analytics
Business performance management (BPM)
extends the monitoring, measuring and comparing of sales, profit, cost, profitability and other performance indicators by introducing the concept of management and feedback. Embraces processes such as planning and forecasting.
User interface / dashboard
Comprehensive visual view or corporate perofrmance measures (KPI), trends and exceptions. Integrate infor from multiple business areas. Present graphs that show actual performance compared to desired metrics. At a glance view of the health of the organisation.
Its major objective is to enable interactive access (sometimes in real time) to data, to enable manipulation of data, and to give business managers and analysts the ability to conduct appropriate analysis.
By analysing current, historical data and situations, performance - decisionmakers get valuable insight that enable them to make more informed and better decisions.
The process of BI is transformation of data to inormation, then to decisions and finally to actions.
4 major components:
Data warehouse
Conerstone of any medium to large BI system. Includes current and historical data.
Business analytics
- Reports and queries: static and dynamic reporting, queries, discovery, multi-dimensional view, drill-down to details.
- Advanced analytics: statistical, mathematical, financial
- Data, text, web mining: Data mining is a process of searching for unknown relationships or information in large databases or data warehouses, using inteligent tools such as neural computing, predictive analysis techniques or advacne statistical methods.
Business performance management (BPM)
extends the monitoring, measuring and comparing of sales, profit, cost, profitability and other performance indicators by introducing the concept of management and feedback. Embraces processes such as planning and forecasting.
User interface / dashboard
Comprehensive visual view or corporate perofrmance measures (KPI), trends and exceptions. Integrate infor from multiple business areas. Present graphs that show actual performance compared to desired metrics. At a glance view of the health of the organisation.
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