Classification Rules and Database Architecture

 

 

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Data classification is the process of sorting and categorizing data into various types, forms or any other distinct class. Data classification enables the separation and classification of data according to data set requirements for various business or personal objectives. It is mainly a data management process.

 

A well-planned data classification system makes essential data easy to find and retrieve. This can be of particular importance for risk management, legal discovery, and compliance.

 

Written procedures and guidelines for data classification should define what categories and criteria the organization will use to classify data and specify the roles and responsibilities of employees within the organization regarding data stewardship.

 

Distributed Relational Database Architecture (DRDA) is a protocol set that allows multiple database systems and application programs to work together. Any combination of relational database management products that use DRDA can be connected to form a distributed database management system.

 

DRDA is a database interoperability standard from an industry consortium called The Open Group. It describes the architecture for distributed data and defines the rules for accessing distributed data. It was initially used in DB2 2.3.

 

DRDA has the following components:

 

Application Requester: Accepts SQL requests from applications and sends them to appropriate application servers for processing. Application programs can access remote data using this function.

 

Application Server: Receives requests from application requesters and processes them. The application server acts on the portions of requests that can be processed, and forwards remainder to database servers for further processing.

 

 

Database Server: Receives requests from the application server and other database servers. This server also supports distributed requests and forwards parts of the request to the database server to fulfill the request.

 

 

 

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Computational Algorithms for Databases

 

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A database-management system (DBMS) is a computer-software application that interacts with end-users, other applications, and the database itself to capture and analyze data. A general-purpose DBMS allows the definition, creation, querying, update, and administration of databases.

 

Computer scientists may classify database-management systems according to the database models that they support; the most popular database systems since the 1980s have all supported the relational model – generally associated with the SQL language. Sometimes a DBMS is loosely referred to as a “database”.

 

Databases can be described as all of the following:

 

Information – sequence of symbols that can be interpreted as a message. Information can be recorded as signs, or transmitted as signals.

 

Data – values of qualitative or quantitative variables, belonging to a set of items. Data in computing (or data processing) are often represented by a combination of items organized in rows and multiple variables organized in columns. Data are typically the results of measurements and can be visualised using graphs or images.

 

Computer data – information in a form suitable for use with a computer. Data is often distinguished from programs. A program is a sequence of instructions that detail a task for the computer to perform. In this sense, data is everything in software that is not program code.

 

A database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner data can be stored, organized and manipulated. The most popular example of a database model is the relational model, which uses a table-based format.

 

 

 

 

 

 

 

 

 

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Database Query Languages

 

 

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Query languages or data query languages (DQLs) are computer languages used to make queries in databases and information systems. Broadly, query languages can be classified according to whether they are database query languages or information retrieval query languages.

 

An information retrieval (IR) query language is a query language used to make queries into database, where the semantics of the query are defined not by a precise rendering of a formal syntax, but by an interpretation of the most suitable results of the query. Of importance in IR query languages is weighting and ranking, ‘relevance-orientation’, semantic relativism and logic-based probabilism.

 

Contextual Query Language (CQL), previously known as Common Query Language, is a formal language for representing queries to information retrieval systems such as search engines, bibliographic catalogs and museum collection information.

 

DML is abbreviation of Data Manipulation Language. It is used to retrieve, store, modify, delete, insert and update data in database. Examples: SELECT, UPDATE, INSERT statements. DDL is abbreviation of Data Definition Language. It is used to create and modify the structure of database objects in database.

 

SQL is used to communicate with a database. According to ANSI (American National Standards Institute), it is the standard language for relational database management systems. SQL statements are used to perform tasks such as update data on a database, or retrieve data from a database.

 

 

Cypher is a very popular declarative query language that was invented by the folks at Neo4j. Its popularity stems from its resemblance to SQL, so those with SQL experience will feel right at home.

 

 

SPARQL is SQL-like declarative query language that was created by W3C to query RDF (Resource Description Framework) graphs.

 

 

GraphQL (created by Facebook) is a query language for APIs that isn’t specific to graph databases. Users define the structure of the data they need and they get exactly what they asked for. GraphQL queries are organized as types and fields, and not as endpoints. By varying the request object, you can determine what gets returned by the server.

 

 

 

 

 

 

 

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Distributed Databases

 

 

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A distributed database is a database in which storage devices are not all attached to a common processor. It may be stored in multiple computers, located in the same physical location; or may be dispersed over a network of interconnected computers.

 

A centralized distributed database management system (DDBMS) integrates the data logically so it can be managed as if it were all stored in the same location.

 

The DDBMS synchronizes all the data periodically and ensures that updates and deletes performed on the data at one location will be automatically reflected in the data stored elsewhere.

 

Distributed databases can be homogenous or heterogeneous.

 

As a result, understanding basic sorting algorithms is a necessary part of certain kinds of computer science work.

 

In a homeogenous distributed database system, all the physical locations have the same underlying hardware and run the same operating systems and database applications. In a heterogeneous distributed database, the hardware, operating systems or database applications may be different at each of the locations.

 

A distributed database can reside on organized network servers or decentralized independent computers on the Internet, on corporate intranets or extranets, or on other organization networks.

 

 

 

 

 

 

 

 

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