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Advanced Databases

Parallel Database: Distributed Database: object-oriented Database: Spatial Database: Deductive Database: Mobile Database: Multimedia Data and Multimedia Databases: Data Warehousing Data Mining

DATA MINING:

Data mining (sometimes called data or knowledge discovery) is the computational  process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Data mining always  depends on effective data collection and warehousing as  computer processing. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified, based upon the end user queries Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Several types of analytical software are available: statistical, machine learning, and neural networks. Generally,

DATA WAREHOUSING:

A data warehouse is a relational database that acts as a repository for archive of information gathered from multiple sources, stored under a unified schema under a single site It is being designed for query, data analysis and reporting rather than for transaction processing. Data warehouses store current and historical data which are derived from transactional data and are used for creating trending reports for senior management reporting A data warehouse environment includes an extraction, transportation, transformation, and loading (ETL) solution, an online analytical processing (OLAP) engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users. The typical Extract-Transform-Load ( ETL )-based data warehouse uses  staging , data integration, and access layers to house its key functions Staging: The staging layer or staging database stores raw data extracted from each of the disparate source data system

MULTIMEDIA DATA AND MULTIMEDIA DATABASES:

Multimedia Data  Multimedia data typically means digital images, audio, video, animation and graphics together with text data Multimedia data can provide more effective dissemination of information in science, engineering, medicine, modern biology, and social sciences. It also facilitates the development of new paradigms in distance learning, and interactive personal and group entertainment. Multimedia Databases A multimedia database may be defined as a one that hosts one or more inter-related multimedia data as the primary contents of the database The main goal of a multimedia database system is to provide a suitable environment for using and managing multimedia database information Common multimedia data types that can be found in a multimedia database include the following: Text Graphics: drawing, sketches, and illustrations Images: color and black & white pictures, photographs, maps and paintings Animation sequences: animated images or graphic objects

MOBILE DATA BASES:

Mobile Database'  is either a stationary  database  that can be connected to by a  mobile computing  device - such as  smart phones  or PDAs - over a  mobile network , or a database which is actually carried by the mobile device. This could be a list of contacts, price information, distance travelled, or any other information. Mobile database systems have to be adapted to the limited resources of current mobile devices. They are small-footprint databases, which use special replication and synchronization algorithms for the communication (up and download) with a centralized, consolidated and hard-wired database. A mobile database uses wireless technology to allow mobile computers to connect to its system. The database consists of a client and server that connect to each other over a wireless network . Due to the vulnerability of wireless network signals, a cache of activity is maintained to ensure that sensitive information can be recovered. A mobile database is used to pro

DEDUCTIVE DATABASES:

In a deductive database system we typically specify rules through a declarative language-A language in which we specify what to achieve rather than how to achieve A model used for deductive databases is closely related to the relational data model. A deductive database uses two main types of specifications namely facts and rules Facts are specified in a manner similar to the way relations are specified except that it is not necessary to include attribute names Rules are similar to relational views.They specify virtual relations that are not actually stored but that can be formed from the facts. A Deductive database is a  database system  that can make  deductions  (i.e., conclude additional facts) based on  rules  and  facts  stored in the (deductive) database. An inference engine within the system can deducenew facts from the database by interpreting theses rules The deductive database works on the principle of logic and has  used prolog as a starting point Deductive da

SPATIAL DATABASES:

A spatial database is a  database  that is optimized to store and query data that represents objects defined in a geometric space. A spatial database stores objects that have spatial characterstics that describe them Most spatial databases allow representing simple geometric objects such as points, lines and polygons. The main extensions that are needed for spatial databases are models that can interpret spatial characterstics. Spatial databases use a  spatial index   to speed up database operations.

OBJECT ORIENTED DATABASES:

An object database (also object-oriented database management system )  is a  database management system  in which information is represented in the form of  objects  as used in  object-oriented programming . An object may be defined as any entity in the real world tha has some characterstics An object has two components namely state(value) and behaviour(operations) Objects exist in two forms given below: Transient objects: Those which exist only during program execution Persistent Objects:Those which exist permenantly The objects may have an object structure of arbitrary comlexity in order to contain all necessary information to describe the object The internal structure of an object in object oriented programming language inlude specification of instance variables Object Oriented Database (OODB) provides all the facilities associated with object oriented paradigm ie  Object-oriented database management systems (OODBMSs) combine database capabilities with  object-oriented

DISTRIBUTED DATABASE:

A logically interrelated collection of shared data  and a description of this data physically distributed over a computer network which can be accessed by any node attached to that network. In a distributed database  storage devices  are not all attached to a common processing unit such as the  CPU  ie, A distributed database system consists of loosely-coupled sites that share no physical components. The software system that permits the management of the distributed database and makes the distribution transparent to users. A Distributed Database Management System (DDBMS) consists of a single logical database that is split into a number of fragments. Each fragment is stored on one or more computers under the control of a separate DBMS, with the computers connected by a communications network. Each site is capable of independently processing user requests that require access to local data (that is, each site has some degree of  local autonomy) and is also capable of processing data

PARALLEL DATABASE:

Parallel processing refers to  a large class of techniques that are used to provide simultaneous data processing tasks for the purpose of increasing the computational speed of a computer system. When a database uses the concept of parallel processing for the execution of transactions inside it,then such a database is called a parallel database. A parallel  database  system seeks to improve performance through  parallelization  of various operations, such as loading data, building indexes and evaluating queries. Parallel databases improve processing and   input/output  speeds by using multiple  CPUs  and disks in parallel. A parallel database system acts as a database server for multiple application servers in client server organization in computer networks. The following are the advantages of parallel database systems. High Performance High Stability Extensibility The general architecture of a parallel database system is shown and the various components are: Session

ADVANCED DATA STRUCTURES LABORATORY

OBJECTIVES: To learn to implement iterative and recursive algorithms. To learn to design and implement algorithms using hill climbing and dynamic programming techniques. To learn to implement shared and concurrent objects. To learn to implement concurrent data structures.   LAB EXERCISES: Each student has to work individually on assigned lab exercises. Lab sessions could be scheduled as one contiguous four-hour session per week or two two-hour sessions per week. There will be about 15 exercises in a semester. It is recommended that all implementations are carried out in Java. If C or C++ has to be used, then the threads library will be required for concurrency. Exercises should be designed to cover the following topics:   1.       Implementation of graph search algorithms. 2.       Implementation and application of network flow and linear programming problems. 3.       Implementation of algorithms using the hill cl