Term
| Three incorrect assumptions about IS Managements |
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Definition
1. Managers will have no problem making decisions if they get the data they need
2. Poor decisions are made because managers lack relevant information
(managers suffer more from information overload)
3. Managers are aware of the data they need |
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Term
| Problems of using operational data for BI Systems |
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Definition
- Dirty Data
- Missing values
- Inconsistent data
- Data not integrated
- Wrong granularity (too fine/not fine enough)
- Too much data (too many attributes, too many data points) |
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Term
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Definition
- Traditional perspective: leading/directing resources of an organization
- Day-to-day management: not very glamorous- involves constant decision making
- Management impacts all aspects of an organization such as operations, customer retention etc. |
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Term
| What do managers need to make decisions? |
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Definition
Data - raw facts
Information - summarized data
Knowledge - relationships among pieces of information
- cause and effect relationships
= price increase on sales, market share
= effect of new manufacturing technology
on product quality |
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Term
| OLTP (Online Transaction Processing) |
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Definition
- Collects data electronically and process transactions online
- Backbone of all functional, cross-functional, and inter-organizational systems in an organization
- Support decision making by providing the raw information about transactions and status for an organization |
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Term
| 2 Types of Transaction Processing |
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Definition
1. Real-time processing
- Transactions are entered and processed immediately
upon entry e.g. airline reservation, banking system
2. Batch Processing
- Systems waits until it has a batch of transactions
before the data are processed and the information is
updated e.g. transfer of all daily branch transactions
to the central office for processing |
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Term
| OLAP (Online analytic processing)/ DSS (Decision support systems) |
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Definition
- Focus on making OLTP-collected data useful for decision making
= provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data
= report has measures (data item of interest, e.g. total sales, average sales, average cost)), or facts, and dimensions (a characteristic of a measure e.g. purchase date, customer type, customer location, and sales region) |
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Term
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Definition
| Although data is collected in OLTP, data may not be used to improve decision making |
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Term
| BI (Business Intelligence) Systems |
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Definition
| Provides information for improving decision making |
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Term
| 4 Categories of BI systems |
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Definition
1. Reporting Systems
2. Data-Mining Systems
3. Knowledge Management Systems
4. Expert Systems |
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Term
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Definition
- Integrate data from multiple sources
- Process data by sorting grouping, summing averaging, and comparing
- Format results into reports
Competitive advantage
Improve decision making by providing right information to right user at the right time |
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Term
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Definition
- Process data using sophisticated statistical techniques
-> Regression analysis, decision tree analysis
- Look for patterns and relationships to anticipate events
or predict future outcomes
Competitive Advantage
- Improve decisions by discovering patterns and relationships in data to predict future outcomes |
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Term
| BI - Knowledge-Management Systems |
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Definition
Share knowledge of products, product uses, best practices etc. among employees, managers, customers and others
Competitive advantage
- improve decisions by publishing employee and others' knowledge
- create value from existing intellectual capital
- Foster innovation, improve customer service, increase organizational responsiveness and reduce costs |
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Term
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Definition
Encode human knowledge in the form of If/Then rules and process those rules to make a diagnosis or recommendation
Competitive Advantage - Improve decisions making by non-experts by encoding, saving and processing expert knowedge |
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Term
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Definition
| Used to extract and clean data from operational systems and other sources, and to store and catalogue that data for processing by BI tools. |
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Term
| Basic components of a data warehouse |
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Definition
| Programs read operational data and extract, clean and prepare that data for BI processing |
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Term
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Definition
- Stores data
- Include data purchased from outside sources
- Metadata concerning data stored in data-warehouse meta database
- Extracts and provides data to BI tools |
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Term
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Definition
A data collection that is created to address the needs of a particular business function, problem, or opportunity
- Smaller than data warehouse
- Users may not have data management expertise
= knowledgeable analysts for specific function |
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Term
| Two categories of data-mining techniques |
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Definition
1. Unsupervised
2. Supervised |
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Term
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Definition
Analysts do not create a model or hypothesis before running the analysis;
But they apply the data-mining technique to the data and observe the results
[create hypotheses after analysis to explain patterns found]
Common unsupervised technique:
Cluster analysis - identify groups of entities that have similar characteristics |
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Term
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Definition
Data miners develop a model prior to the analysis and apply statistical techniques to data to estimate parameters of the model
Examples
Regression analysis
Neural networks |
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Term
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Definition
| Measures the impact of a set of variables on another variable |
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Term
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Definition
| Used to predict values and make classifications, e.g. "good prospect" or "poor prospect" |
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Term
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Definition
To determine sales pattern
Shows the products that customers tend to buy together |
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