This document outlines the process of data mining using Microsoft Access, focusing on extraction, transformation, and loading (ETL) techniques. It describes the tools required, including MS Excel and a MySQL conversion tool, as well as step-by-step instructions for data preparation, import, cleaning, and conversion to SQL format for use on a database server. The overall goal is to demonstrate how to transition a document-based database into a structured SQL format for analysis.

1. Data Mining with MS Access<br />This documentation is to support the presentation given on Data Mining using Microsoft Access. Step wise description is given below –<br />Purpose of this project – <br />To demonstrate the process of Extraction, Transformation and Loading (ETL).<br />Tools required – <br />MS Excel - contains source data.<br />MS Access for formatting, standardizing, cleaning, converting and changing data in the required state.<br />Access to MySql conversion tool is a tool that converts the imported Excel data on MS Access to SQL script file (.sql file). The sql script file consists of the code for creating tables of MS Access as well as the complete data.<br />Php MyAdmin server to load the database on the server.<br />Technique used – <br />This entire process is done using the ETL technique. <br />Extraction of data involves collecting data from various data sources.<br />Transformation of data involves cleaning, converting, standardizing formatting the data as required.<br />Loading data onto a destination database in a data warehouse or on a database server.<br />All these processes are inter-dependent.<br />The following steps will give a brief description of the snapshots shown in the presentation –<br />Check which excel data file has to be extracted and remove filter to avoid any loss or discrepancies while extracting data.

2. Prepare data for extraction without filter.