A study on microsoft SQL server 2000 / Ireen Munira Ibrahim

Ibrahim, Ireen Munira (2003) A study on microsoft SQL server 2000 / Ireen Munira Ibrahim. Degree thesis, Universiti Teknologi MARA.

Abstract

The past two decades has seen a dramatic increase in the amount of information or data being stored in electronic format. Handling data in small amounts is easier for the
company or organization but when the data becomes larger and huge, they faced the difficulties in retrieving and analyzing the information they needs. Even though the data
are converted and represented in computer format, the analysis of data needs to be done manually because our capability of analyzing and understanding massive amounts of data lags far behind our ability to gather and store the data. This study focuses on how to develop relational database by using Microsoft SQL Server 2000 in where this software can handle large amounts of data. In this study also new Microsoft Corp. product named Microsoft Analysis Services have been studied for analysis and prediction process. This software has provided data mining models. Data Mining is thought to be far superior than existing data analysis tools. This data mining is an AI tool that is used to predict and analyzing unknown features. This study also intends to investigate how to develop relational database and its operation such as creating, deleting, updating and retrieving by using Microsoft SQL Server 2000. Then the weaknesses of this software will be studied.
Perhaps, the findings of this study are able to help people in the future

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Ibrahim, Ireen Munira
UNSPECIFIED
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Keywords: Microsoft SQL Server 2000, information, data mining, database
Date: 2003
URI: https://ir.uitm.edu.my/id/eprint/9337
Edit Item
Edit Item

Download

[thumbnail of TD_IREEN MUNIRA IBRAHIM CS 03_5.pdf] Text
TD_IREEN MUNIRA IBRAHIM CS 03_5.pdf

Download (73kB)

Fulltext

Fulltext is available at:

ID Number

9337

Indexing

|

Statistic

Statistic details