DATA

By Aspet Galestanian05/08/2010

What is Data

Data is information that has been translated into a form that is more convenient to move or process.

Meaning of data, information and knowledge

The terms information and knowledge are frequently used for overlapping concepts. The main difference is in the level of abstraction being considered. Data is the lowest level of abstraction, information is the next level, and finally, knowledge is the highest level among all three

Example

Data on its own carries no meaning. In order for data to become information, it must be interpreted and take on a meaning. For example, the height of Mt. Everest is generally considered as "data", a book on Mt. Everest geological characteristics may be considered as "information", and a report containing practical information on the best way to reach Mt. Everest's peak may be considered as "knowledge".

Transitions from data, to information, to knowledge

Importance of data

Most research projects need data in order to answer a proposed research problem. The data that need to be acquired, and the sources of such data, must be identified as a matter of utmost importance.

Data Management

is a broad field of study, but essentially is the process of managing data as a resource that is valuable to an organization or business.

Main Topics in Data management Data Modeling Data Warehousing Data Movement Database Administration Data Mining

Data Modeling

Data modeling is first creating a structure for the data that you collect and use and then organizing this data in a way that is easily accessible and efficient to store and pull the data for reports and analysis.

The data modeling process

Modeling methodologies

Top-down

Bottom-up:

Entity relationship diagrams

Techniques for data modeling

Semantic data modeling Generic data modeling Data Vault Modeling Object-Relational Mapping Object Role Modeling Relational Model

Semantic data modeling

It’s technique to define the meaning of data within the context of its interrelationships with other data.

Data Warehousing

A data warehouse is a repository of an organization's electronically stored data. Data warehouses are designed to facilitate reporting and analysis

Advantages

Provides a common data model for all data of interest regardless of the data's source.

Information in the data warehouse is under the control of data warehouse users so that, even if the source system data is purged over time, the information in the warehouse can be stored safely for extended periods of time.

Because they are separate from operational systems , data warehouses provide retrieval of data without slowing down operational systems.

Data warehouses can work in conjunction with and, hence, enhance the value of operational business applications, notably Customer Relationship Management (CRM) systems.

Data warehouses facilitate decision support system applications such as trend reports

Disadvantages

Data warehouses are not the optimal environment for unstructured data.

latency High costs. Data warehouses can get outdated

relatively quickly

Data Movement

Data movement is the ability to move data from one place to another.

What is DBMS

To access information from a database, you need a database management system This is a collection of programs that enables you to enter, organize, and select data in a database.

A DBMS is a set of software program that controls the organization, storage, management, and retrieval of data in a database.

History

1960s Navigational DBMS

1970s Relational DBMS

End 1970s SQL DBMS

1980s Object Oriented Databases

Components of DBMS

DBMS Engine Data Definition Subsystem Data Manipulation Subsystem Application Generation Subsystem Data Administration Subsystem

Different Type of DBMS Relational Database Management

Systems

Network Database Management Systems

Hierarchical Database Management Systems

Primary tasks of DBMS packages

Database Development

Database Interrogation

Database Maintenance

Application Development

Advantage of DBMS

Advantages: Control of data redundancy, consistency,

abstraction, sharing Improved data integrity, security,

enforcement of standards and economy of scale.

Balanced conflicting requirements Improved data accessibility, responsiveness,

maintenance Increase productivity, concurrency, backup

and recovery services.

Disadvantges of DBMS

Complexity, size, cost of DBMSs Higher impact of a failure

Data mining

Data mining is a process in which large amounts of data are sifted through to show trends, relationships, and patterns.

Adv.(from IBM)

http://www.youtube.com/watch?v=AnL98lQdqa8

References

http://www.articlesnatch.com/Article/History-Of-The-Database-Management-System/307676

http://math.hws.edu/vaughn/cpsc/343/2003/history.html http://en.wikipedia.org/wiki/Database_management_syste

m http://searchdatamanagement.techtarget.com/definition/d

ata http://www.systems-thinking.org/dikw/dikw.htm http://www.earthresearch.com/data-importance.shtml

Thank you