Final Flashcards
(123 cards)
What are the steps in decision making
- Intelligence gathering
- Alternative formulation
- Choice
- Implementation
- Review
What are the decision making challenges
• Factors that make business decision making challenging
– Uncertainty and complexity
– Information overload
– Data quality
What do managers need to make decisions
– 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
– What is beyond knowledge? Imagination or vision
• E.g.,of future business direction
• Cannot be mimicked by computers
• Formation of a business vision triggers knowledge gathering processes which then guide decision-making
How does IS help decision making
Information Systems are valuable to the extent they help augment (not replace) the knowledge of managers about their business environment during decision-making
What are the problems with operational data
• Raw data usually unsuitable for sophisticated reporting or data mining
– Dirty data
– Values may be missing
– Inconsistent data
– Data not integrated
– Data can be too fine or too coarse (granularity)
– Too much data
• curse of dimensionality
• too many rows
What is OLTP and how does it support decision making?
• Online Transaction Processing (OLTP) system collects data electronically and process the transactions online
• Backbone of all functional, cross-functional, and inter-organizational systems in an organization
• OLTP systems support decision making by providing the raw information about transactions and status for an organization
What are the two types of transaction processing
• Real-time processing
– Transactions are entered and processed immediately upon entry
• Examples: airline reservation systems, banking systems
• Batch processing
– System waits until it has a batch of transactions before the data are processed and the information is updated
• Example: transfer of all daily branch transactions to the central office for processing
Explain online analytical processing
• While data may be collected in OLTP, the data may not be used to improve decision making
• Online Analytic Processing (OLAP) systems focus on making OLTP- collected data useful for decision making
– OLAP provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data
– OLAP report has measures, or facts, and dimensions
Is Data an Asset?
• What is an Asset?
– Something that can be used by an organization to produce a benefit
• Data as an Asset
– Reusable
– Low storage cost
– Used to improve revenue or decrease costs, and improve decisions
– Provides Organizational Memory
How do BI systems provide competitive advantages?
• Business Intelligence (BI) system provides information for improving decision making
• Primary systems:
– Reporting systems
– Data-mining systems
– Knowledge-management (KM) systems
– Expert systems
Explain reporting systems
• Integrate data from multiple sources
• Process data by sorting, grouping, summing, averaging, and
comparing
• Format results into reports
• Improve decision making by providing right information to right user at right time
Explain data mining systems
• Process data using sophisticated statistical techniques
– Regression analysis
– Decision tree analysis
• Look for patterns and relationships to anticipate events or predict future outcomes
– Market-basket analysis
– Predict donations
Explain Knowledge management systems
• Create value from intellectual capital
• Collect and share human knowledge
• Supported by the five components of the information system • Foster innovation
• Improve customer service
• Increase organizational responsiveness
• Reduce costs
Explain Expert systems
• Encapsulate the knowledge of human experts in the form of If/Then rules
– If condition is true, Then initiate procedure
• Improve diagnosis and decision making in non-experts
Characteristics and Comp Advantages
Slide 23 lesson 7
What is a data warehouse
• Data Warehouse is used to extract and clean data from operational systems and other sources
• Prepares data for BI processing
• Data-warehouse DBMS
– Stores data
– May also include data from external sources
– Metadata concerning data stored in data-warehouse meta database
– Extracts and provides data to BI tools
What are the components of a date warehouse
Data warehouse Metadata
Data warehouse Database
See slide 25 lecture 7
What is datamart
• Data Mart is a data collection
– Created to address particular needs
• Business function
• Problem
• Opportunity
– Smaller than data warehouse
– Users may not have data management expertise
• Knowledgeable analysts for specific function
Review slides 27 and 28 lecture 7
Yes
What are the characteristics and categories of data mining systems
• Data mining is the application of statistical techniques to find patterns and relationships among data and to classify and predict
• Knowledge discovery in databases (KDD)
• Take advantage of developments in data management
• Two categories:
– Unsupervised
– Supervised
Explain unsupervised data mining
• Analysts do not create model or hypothesis before running the analysis
• Apply data-mining technique to the data and observe results
• Hypotheses created after analysis as explanation for results
• Example:
– Cluster analysis
• identify groups of entities that have similar characteristics
Explain supervised data mining
• Model developed before the analysis
• Statistical techniques applied to data to estimate parameters of the
model
• Examples:
– Regression analysis
• measures the impact of a set of variables on another variable
– Neural networks
• used to predict values and make classifications, such as “good prospect” or “poor prospect” customers
What is database marketing
• You have the applications, the database and data warehouse etc…. Now you need to use it!
• One way of using it is to understand customer to achieve intimacy and increase effectiveness of marketing.
• Techniques for using data to build a stronger relationship with customers and differentiating products and services
– One-to-one marketing – Transactive contents
What is one to one marketing and what is it suitable for
• Segment the market on the basis of individuals based on precise and timely understanding of their needs, targeting specific marketing messages to these individuals, and then positioning the product to be truly unique
• Ultimate form of market segmentation where the segments are individuals
• It’s suitable for products:
1. that can be produced in very complex forms,
depending on individual tastes
2. whose price can be adjusted to the level of personalization
3. were the individual’s tastes and preference can be effectively gauged
• Is it nearly as good as personal attention?