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24 Cards in this Set
- Front
- Back
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What is Data |
raw unorganized Facts |
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What is Information |
Transformation of Data into meaning |
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Examples of Data |
Orders processed How much of x is in stock Quantity Sold course enrollment customer name discounts |
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Examples of Information |
-Using Ballpark data to send out personalized promotions -using crime stats to deploy law enforcement to high crime areas |
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What is a transaction |
An exchange between actors |
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What is transactional data |
Data that explains an event in real time Used for everyday events supports management of an organizations data |
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Relational Paradigm |
How transactional data is collected and stored |
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Primary goal of Relational Paradigm |
Reduce Errors and use less space Using less space less of an issue |
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Dimensional Paradigm |
Data stored around an event and then summarized |
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Characteristics of an operational Data store |
Store real time data Based off of relational paradigm optimize data for storage and efficiency support day to day operations |
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Analytical Data Store and Goal |
Based on dimensional paradigm Storage of historical transactional data optimized for data retrieval and summerization GOAL Supports managerial decision-making for periodical analysis |
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Relationship between operational and analytical data store |
Operational data store retrieves and organizes data for day to day activities analytical data store analyzes that data and puts it to use |
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What does a model do, describe, and explain |
It is a representation of the information to be captured describes the data contained in the database Describes how the data interrelates |
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System Analysis |
Process of modeling the problem Requirements oriented Define and Understand |
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Question we are asking ourselves when performing system analysis |
What should we do? |
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Systems Design |
Process of modeling a design Funcationality oriented Where we implement a design |
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Question we ask ourself when performing a system design |
How should we do it |
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Normalization |
Organizing data to reduce redundency |
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Why is Normalization good? 5 reasons |
Reduces redundencies Data takes up less space Makes data easier to navigate Fewer inconsistencies Easier to make changes to data |
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Atomic |
Can't break up data anymore |
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1 to many rule |
Primary key from one goes into many entity as foreign key |
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Many to many rule |
Create new table Primary keys in both tables are foreign keys in new table one to many relationships with original table |
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one to one rule |
Primary keys in other fields as foreign key |
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Example of many to many: Order many to product many, what is the new table and cardinality between the two? |
New table is order-product
one to many towards new table, one to one on old tables |
