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