ONLINE ANALYTIC PROCESSING BY USING MYSQL

Online Analytic Processing By Using MYSQL

Declaration of Originality

This project is all my own work and has not been copied in part or in whole from any other source except where duly acknowledged. As such, all use of previously published work (from books, journals, magazines, internet, etc) has been acknowledged within the main report to an entry in the References list. I agree that an electronic copy of this report may be stored and used for the purposes of plagiarism prevention and detection. I understand that cheating and plagiarism constitute a breach of University Regulations and will be dealt with accordingly. I understand that cheating and plagiarism constitute a breach of University Regulations and will be dealt with accordingly.

Signed:Date:

Abstract

The SQL (Structured Query Language) is actually accessible in most database administration schemes and is the aim of an strong standardization method producing in the newest type of the MYSQL standard. Standards are basic, but often they are tough to use, due to their need of understandability and the incident of inconsistencies. An ontology is helpful for clarifying the components of a benchmark, along with their interrelationships, as well as for noticing inconsistencies. In this paper we suggest an ontology for the object-relational characteristics of the new MYSQL benchmark, formalized with UML 2.0 class design drawings and OCL well-formedness rules. The ontology is instantiated with an demonstration in which most of the new object-relational characteristics of the MYSQL benchmark are presented.

 

Online Analytic Processing By Using MYSQL

Introduction

Online Analytical Processing (OLAP) databases help business-intelligence queries. OLAP is a database expertise that has been optimized for querying and describing, rather than of processing transactions. The source data for OLAP is Online Transactional Processing (OLTP) databases that are routinely retained in data warehouses. OLAP data is drawn from from this chronicled data, and aggregated into organisations that allow complicated analysis. OLAP data is furthermore coordinated hierarchically and retained in cubes rather than of tables. It is a complicated expertise that values multidimensional organisations to supply fast get access to to data for analysis. This association makes it so straightforward for a PivotTable report or PivotChart report to brandish high-level abstracts, for example sales sums over an whole homeland or district, and furthermore brandish the minutia for sites where sales are especially powerful or weak.

OLAP databases are conceived to pace up the retrieval of data. Because the OLAP server, other than Microsoft Office Excel, computes the summarized standards, less data desires to be dispatched to Excel when you conceive or change a report. This set about endows you to work with much bigger allowances of source data than you could if the data were coordinated in a customary database, where Excel retrieves all of the one-by-one Notes and then calculates the summarized values.

OLAP databases comprise two rudimentary kinds of data: assesses, which are numeric data, the amounts and averages that you use to make acquainted enterprise conclusions, and proportions, which are the classes that you use to coordinate these ...