Chapter 5 Summary

Difficulties in Managing Data:

• Increase rapidly.
• Are scattered.
• Are come from many sources.
• Data security quality are critical.
• Some information systems are not communicate with each other.
• Data Degrades overtime.
• Data rot.

 

To solve this difficulties of data we use DBMS

- Data management system will minimize:

• Data repeated.
• Separate Data/ not linking data.
• Data isolation.
• Data inconsistency

- Data management system will maximize:

• Safety of data/ data security.
• Data integrity.
• Data Independence.

 Data Hierarchy:        
 

                      See this video                      

Bit: smallest unit of data a computer can handle.

Byte: eight bits and represents a single character

Field: is a group of related characters/ the heading of the columns.

Record:  a group of logically related fields.

File: a group of related records.

Database: a group of related files.

Data model:

A diagram that represents the entities in the database and their relationships.

 

Foreign Key; A field in one table that uniquely identifies a row (record) of another table. It is used to establish and enforce a link between two tables.

 ER diagrams: consists of entities, attributes and relationships.
 

• One-to-One [1:1]
• One-to-Many [1:M]
• Many-to-Many [M:M]

 

Requesting Data from a database:

Structured Query Language (SQL):
Allows users to perform complicated searches (request information) by using relatively simple statements or keywords. 

Query by Example (QBE): 

Allows users to fill out a grid or template to construct a sample or description of the data he or she wants.

Data Dictionary:

• Defines the format necessary to enter the data into the database.
• Provides information on each attributes. 
• Provides information on how often the attribute should be updated . 

Normalization & Non-Normalization:

Normalization: Organize table and use the information according to the name of table. (separate)

Non-Normalization: Does not organize the table and use all the information together/ different information. (mixed)

  The profits of Normalization:           

• Reduce redundancy.
• Increase Data integrity.
• Best processing.

Data warehouse:

Data is stored in one big place. Collection of current and historical data.

Benefits of data warehouse:

• The users can access and process data on line, easily and quickly.
• Analysis data in way that is not possible before.
• Get the all results or report from the organization.

Problems with data warehouse:

• very expensive to build.
• Keep the system difficult.
• Don not keep people to share data with other department.

Data mart:

A small data warehouse, designed for the end-user needs in a strategic business unit (SBU) or a department.

Benefits of data mart:

• less costly than a data warehouse (around R.O. 40, 000)
• Can be implemented more quickly (around 3 months)
• More rapid response and easier to learn and navigate.

Knowledge management (KM):

Is a process supported by IS. (Transfer knowledge from individual knowledge to organization knowledge).

 Benefits of KM:

• Free flow of idea.
• better way to solving problems.
• Achieve revenue.
• Develop retention  rate.

KM cycle: