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Database Architecture

data architecture is composed of models, policies, rules or standards that govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations.Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture.

There are three levels of database architecture.These includes:

  • External Level – concerned with the way users perceive the database.
  • Conceptual Level – concerned with abstract representation of the database in its entirety.
  • Internal Level – concerned with the way data is actually stored.

Database architecture uses programming languages to design a particular type of software for businesses or organizations.Database architecture focuses on the design, development, implementation and maintenance of computer programs that store and organize information for businesses, agencies and institutions. A database architect develops and implements software to meet the needs of users.

The design of a DBMS depends on its architecture. It can be centralized or decentralized or hierarchical. The architecture of a DBMS can be seen as either single tier or multi-tier. As shown below :

Data Independence

  1. Logical Data Independence – users and user programs are independent of logical structure of the database
  2. Physical Data Independence – the separation of structural information about the data from the programs that manipulate and use the data i.e. the immunity of application programs to changes in the storage structure and access strategy
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Introduction to Database

A Database is an organized collection of logically related data. The purpose of database is to store information about certain types of objects termed entities or objects.

A database is a shared collection of logically related data designed to meet the information needs of an organization.

Components of Database Systems

  1. Database
  2. Hardware
  3. Software – DBMS
  4. Procedures
  5. Users
  1. Database

The data in the database will be expected to be both integrated and shared particularly on multi-user systems

Integration – The database may be thought of as a unification of several otherwise distinct files, with any redundancy among these files eliminated

Shared – individual pieces of data in the database may be shared among several different users

  • Data: Refers to stored representations of meaningful objects and events. Includes Structured: numbers, text, dates
    • Unstructured (multimedia): images, video, documents
  • Information: Refers to data processed to increase knowledge of the person who uses the data place data in a context
    • Involves summarizing, processing and presentation of data
  • Metadata-Is data that describes the properties or characteristics of user data.It is the primary mechanism for providing context for data.Data without metadata can be confusing, misinterpreted, or erroneous
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2.Hardware

These are secondary storage on which the database physically resides, together with the associated I/O devices, device controllers etc.

3.Procedures

These are instructions and rules that govern design and use of databases e.g. starting and stopping database, making backups, handling failures.

4. Users and their Roles

  • Database Designers – designs conceptual and logical database
  • Application Developers  – writes application programs that use the database
  • Data and Database Administrator
  • End – user – interacts with the system from an on-line   terminal by using Query Languages etc.

Data and Database Administration

  1. Data Administrator – Is a business manager responsible for controlling the overall corporate data resources
  2. Database Administrator (DBA) – Is a technical person responsible for development of the total system

Advantages of the Database Approach

  • Program-data independence: the separation of data description from the application program; metadata is stored in central repository
  • Planned data redundancy:  Control of data redundancy
  • Improved data consistency
  • Improved data sharing and productivity
  • User view: a logical description of some portion of the database that is required by a user to perform some task
  • Increased application development productivity
  • Enforcement of standards
  • Naming conventions, data quality standards and uniform procedures for accessing, updating and protecting data
  • Improved data quality
  • Integrity constraints
  • Improved data accessibility and responsiveness
  • SQL (structured query language) can be used to extract meaning from data.
  • Reduced program maintenance
  • Improved decision support
  • Multipurpose use of data
  • Balance conflicting user requirement
  • Improved data accessibility and responsiveness
  • Improved maintenance through data independence
  • Increased concurrency
  • Improved backup and recovery services.

Disadvantages: – Costs and Risks of the Database Approach

  • Complexity
  • Size
  • Cost of DBMS : Installation and management cost and complexity
  • Additional hardware costs
  • New, specialized personnel
  • Conversion costs
  • Need for explicit backup and recovery
  • Organizational conflict.