GDL

Pattern Emission by Nobelium Streams

ISSN-2223-4985
Journal from gdlhub / 2012-06-22 15:01:30
Oleh : SarathChand P.V , VenuMadhav K , VenuMadhav K , Prasadu Reddi , Benarji T, International Journal of Information and Communication Technology Research
Dibuat : 2012-06-22, dengan 1 file

Keyword : Entrepreneur, pattern matching, streams, buzzwords, integration methods, exponential methods, computational capabilities
Url : http://esjournals.org/journaloftechnology/archive/vol1no4/vol1no4_2.pdf
Sumber pengambilan dokumen : Internet

The business requirements of an enterprise at a given time depend on the business requirements of the enterprise, the

available technology at that time and also with the accumulated investments of the enterprise from the past technologies.

Generally the business requirements of the business are constantly changing and the changes are at an exponential rate.

The technology has advanced by delivering the exponential increase in the computational power and the communicational

capabilities and the design of the data ware houses. The paper concentrates on the Enterprise Architecture thus far have

displayed and the general inability to gracefully evolve the line with the business requirements and without compromising

the prior technologies, investments and seriously the limiting factors of the organization to evolve further.

The handling features of data retrieval methods are compromising the development mechanisms in the database systems

and with many new applications. The paper illustrates the new knowledge discovery techniques. The paper mainly

concentrates on the new buzzwords, new methodologies and evaluate the new tools which maintains the ties with

technology partners. Now-a-days the data bases must first shift to the puzzle technology to find the pieces that meets the

needs of the business enterprise then integrate the new pieces with the existing ones to form a coherent whole. The paper is

mainly concentrates on the recognition of data retrieval methods in the form of patterns by using the existing technologies.

The pattern emission is performed by a flow of data at a time which are streams. The data is retrieved in the form of

streams so that un-necessary data can be avoided with the pattern matching and the methods of retrieval of data in a very

fast and efficient manner.

Deskripsi Alternatif :

The business requirements of an enterprise at a given time depend on the business requirements of the enterprise, the

available technology at that time and also with the accumulated investments of the enterprise from the past technologies.

Generally the business requirements of the business are constantly changing and the changes are at an exponential rate.

The technology has advanced by delivering the exponential increase in the computational power and the communicational

capabilities and the design of the data ware houses. The paper concentrates on the Enterprise Architecture thus far have

displayed and the general inability to gracefully evolve the line with the business requirements and without compromising

the prior technologies, investments and seriously the limiting factors of the organization to evolve further.

The handling features of data retrieval methods are compromising the development mechanisms in the database systems

and with many new applications. The paper illustrates the new knowledge discovery techniques. The paper mainly

concentrates on the new buzzwords, new methodologies and evaluate the new tools which maintains the ties with

technology partners. Now-a-days the data bases must first shift to the puzzle technology to find the pieces that meets the

needs of the business enterprise then integrate the new pieces with the existing ones to form a coherent whole. The paper is

mainly concentrates on the recognition of data retrieval methods in the form of patterns by using the existing technologies.

The pattern emission is performed by a flow of data at a time which are streams. The data is retrieved in the form of

streams so that un-necessary data can be avoided with the pattern matching and the methods of retrieval of data in a very

fast and efficient manner.

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