Computer Science 1032A/B Chapter Notes - Chapter 8: Online Transaction Processing, Batch Processing, Information Overload
13 Oct 2016
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Computer Science 1032 Chapter 8
Challenges of Making Decisions
- Decision making is a daily occurrence for business managers
- Factors making business decisions challenging
o Uncertainty and complexity
o Information overload
o Data Quality
What are the Challenges Managers Face in Making Decisions?
Information Overload
- “torage Capait Ireases ↑
- Cost Dereases ↓
- Basically unlimited today
- Exponential growth
o Both inside and outside of organizations
o Used to improve decision making
- Ability to store any size customer data
- Allows for a better understanding of the customers
- Data can be used for forecasting
- Competitive strength
o When making decisions
- Busiess Maager’s Challege
o Find appropriate data
o Incorporate this data into decision making
- Information Systems
o Help
o Hinder
Data Quality
- (Processed) Data from operational systems can be used for
o Basic reports
o Example: Current Sales, Sales Projections
- Raw data unsuitable for sophisticated reporting or data mining
- Dirty data – problematic data, missing values, and inconsistent data are problems
- Data granularity – refers to the degree of summarization or detail
- Coarse data – highly summarized, fine data – express details that are too precise
- Example: clicking behavior of clients = clickstream data
What is OLTP and How Does it Support Decision Making?
- Online Transaction Processing TP) system
o Collects data electronically
o Processes the transactions online
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- Backbone of all functional, cross-functional, and interorganizational systems in an
organization
- OLTP systems support decision making
o Provides raw information about transactions
o Provides information about status for an organization
Transaction Processing
- Real-Time processing
o Transactions are entered and processed immediately upon entry
▪ Examples: airline reservation, banking
- Batch Processing
o 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
Online transaction processing (OLTP)
– collecting data electronically and processing the transactions online
– backbone of all functional functional, cross-functional, and interorganizational systems
in an organization
– OLTP systems support decision making by providing raw information about transactions
and providing information about status for an organization efficiently
Real-time processing
Transactions are entered and processed immediately upon entry
Examples: airline reservation, banking
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
What are OLAP and the Data Resource Challenge
Data Resource Challenge:
- While data may be collected in OLTP, the data may not be used to improve decision
making
- Must decide if data as an Asset?
o Asset: Resource from which future economic benefits may be obtained
o How is data valued in an organization? Who manages it? Where is the data?
o Need to treat data as an important resource
OLAP – Online Analytic Processing
- 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, or facts, and dimensions
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find more resources at oneclass.com
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COMPSCI 1032A/B Full Course Notes
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Document Summary
Decision making is a daily occurrence for business managers. Factors making business decisions challenging: uncertainty and complexity. Exponential growth: both inside and outside of organizations, used to improve decision making. Ability to store any size customer data. Allows for a better understanding of the customers. Busi(cid:374)ess ma(cid:374)ager"s challe(cid:374)ge: find appropriate data. Data quality (processed) data from operational systems can be used for: basic reports, example: current sales, sales projections. Raw data unsuitable for sophisticated reporting or data mining. Dirty data problematic data, missing values, and inconsistent data are problems. Data granularity refers to the degree of summarization or detail. Coarse data highly summarized, fine data express details that are too precise. Example: clicking behavior of clients = clickstream data. Online transaction processing tp) system: collects data electronically, processes the transactions online. Backbone of all functional, cross-functional, and interorganizational systems in an organization. Oltp systems support decision making: provides raw information about transactions, provides information about status for an organization.
