The implementation of web based system for the improvment of good governance in the development of rwandan districts.

2.3. Database concepts

2.3.1. Definition and terminology 2.3.1.1 Definition

A database is a collection of information related to a particular subject or purpose.( RIHARD, T. WATSON,» DATA MANAGEMENT : Databases and Organization « , 3^rd edition .p25) .

Data refers to pieces of information or facts usually collected as the result of experience, observation or experiment, or processes within a computer system, or a set of premises.

( Retrieved March 21.2009.from; http// www.wikipedia.org/wik/data)

Information is data that has been processed in a way that it makes it meaningful. Databases are designed to provide meaningful information .This information can only be provided if appropriate data exists in the database and the database is structured in such a way to support that information(PRESCOTT,M,& ALL « Modern Database Management»,5 edition, Addison Wesley Lonman , Inc, May 1999.p 4.)

2.3.1.2. Terminology

A. Entities and Relationships

The very basics of what we are trying to model are entities and relationships. Entities are things in the real world that we will store information about in the database. Relationships are the links between these entities. Relationships come in different degrees. They can be one-to-one, one-tomany (or many to one depending on the direction you are looking at it from), or many to many. (GERAL V .POST «Database Management Systems, Designing and Bulding Business Applications 1^st edition P34.)

Note that the entities, the relationships, and the degree of the relationships depend on your environment and the business you are trying to model. When you are coming up with a database design, you must take these rules into account for the system you are modeling .No two systems will be exactly the same.

B.Relations

In the relational model of databases, a set of tuples (also called rows), otherwise known as a table.

C. Columns or Attributes

An attribute represents the basic abstraction of a database table column. In database tables each column or attributes describes some piece of data that each record in the table has .The terms column and attributes are used fairly interchangeably, but column is really part of a table, whereas an attribute relates to the real - world entity that the table is modeling.

(RetrievedMarch21.2009.from; http://publib.Boulder./ bm.com/inforcenter/db2/MW/V8/index.jsp ?topic=/com./bm.db2.vdb.olap.doc/cmd attribute.htm.)

D. Rows, Records, Tuples

In the context of a relational database, a row also called a record or tuple represents a single, implicitly structured data item in a table. Each row in a table represents a set of related data, and every row in the table has the same structure. (Retrieved March 21.2009.from; http// www.wikipedia.org/wik/row).

E. Keys

i) Primary key:

A primary key is a field or combination of fields that uniquely identify a record in a table, so that an individual record can be located without confusion. (Retrieved March 21.2009.from; http:// databasev.co.uk/ primary- foreign-key-constraints.html ,).

ii) Foreign key

A foreign key (sometimes called a referencing key) is a key used to link two tables together. Typically you take the primary key field from one table and insert it into the other table where it becomes a foreign key (it remains a primary key in the original table).

(Retrieved from March 21.2009.from,http://databasev.co.uk/ primary- foreign-keyconstraints.html ,)

2.3.2. Database design principles 2.3.2.1 Redundancy

Data redundancy is a data organization issue that allows the unnecessary duplication of data within your database. (Retrieved March 21.2009.from http://databasev.co.uk/ primary- foreignkey-constraints.html).

A change or modification, to redundant data, requires that you make changes to multiple fields of a database.

2.3.2.2 Anomalies

Anomalies present a slightly more complex concept. Anomalies are problems that arise in the data due to a flaw in the database design. There are three types of anomalies that may arise:

A. Insertion Anomalies

It is a failure to place information about a new database entry into all the places in the database where information about the new entry needs to be stored.

(Retrieved March 21.2009.from , http://www.dbnormalization.com /database-anomalies,)

In a properly normalized database, information about a new entry needs to be inserted into only one place in the database, in an inadequately normalized database, information about a new entry may need to be inserted into more than one place, and human fallibility being what it is, some of the needed additional insertions may be missed.

B. Deletion anomalies

needs to be deleted from only one place in the database, in an inadequately normalized database, information about that old entry may need to be deleted from more than one place.

(Retrieved March 21.2009.from , http://www.dbnormalization.com /database-anomalies,)

C .Update Anomalies

An update of a database involves modifications that may be additions, deletions, or both. Thus «update anomalies» can be either of the kinds discussed above.

All three kinds of anomalies are highly undesirable, since their occurrence constitutes corruption of the database. Properly normalized database are much less susceptible to corruption than are un-normalized databases. (Retrieved March 21.2009.from , http://www.dbnormalization.com /database-anomalies,)

2.3.2.3 Null Values

A final rule for good database design is that we should avoid schema designs that have large numbers of empty attributes.

2.3.3 Normalization

Normalization is a method of organizing your data to prevent redundancy. Normalization involves establishing and maintaining the integrity of your data tables as well as eliminating inconsistent data dependencies. (Retrieved March 21.2009.from , http://www.databasev.co.uk/ data-redundancy.html,)

Normalization requires that you adhere to rules, established by the database community, to ensure that data is organized efficiently. These rules are called normal form rules.

The rules are defined as follows:

(Retrieved March 21.2009.from , http://en. wikipedia.org/wiki/Normal forms ,)

2.3.3.1. First normal form (1 NF)

Table faithfully represents a relation and has no "repeating groups".

2.3.3.2. Second normal form (2NF)

No non-prime attribute in the table is functionally dependent on a part (proper subset) of a

candidate key.

2.3.3.3 .3rd normal form (3NF)

Every non-prime attribute is non-transitively dependent on every key of the table.

2.3.3.4. Boyce-Codd normal form (BCNF)

Every non-trivial functional dependency in the table is a dependency on a superkey.

2.3.3.5. Fourth normal form (4NF)

Every non-trivial multivalued dependency in the table is a dependency on a superkey.

2.3.3.6. Fifth normal form (5NF)

Every non-trivial join dependency in the table is implied by the superkeys of the table.

2.3.3.7. Domain/key normal form (DKNF)

Every constraint on the table is a logical consequence of the table's domain constraints and key

constraints.

2.3.3.8. Sixth normal form (6NF)

Table features no non-trivial join dependencies at all (with reference to generalized join

operator).

2.3.4. Database management system

A database management system (DBMS) is computer software that manages databases. DBMS's may use any of a variety of database models, such as the network model or relational model. In large systems, a DBMS allows users and other software to store and retrieve data in a structured way.

(Retrieved March 22.2009. from, http://wikipedia.org/wiki/Database-management-system,)

2.3.5. Data processing architecture

Data architecture describes the data structures used by a business and/or its applications. There are descriptions of data in storage and data in motion; descriptions of data stores, data groups and data items; and mappings of those data artifacts to data qualities, applications, locations etc. (Retrieved March 22.2009. from , http://wikipedia.org/wiki/Data-architecture).

Essential to realizing the target state, Data Architecture describes how data is processed, stored, and utilized in a given system. It provides criteria for data processing operations that make it possible to design data flows and also control the flow of data in the system.