Download Data Warehouse Project Data Mining Project

Data Warehouse Project
Title : Datamart and OLAP operations on Company Data Warehouse
Data set : Company Schema in Navathe textbook for Database
Objective:
The main objective of data warehouse project to create a data mart and perform OLAP
operations to gain information.
Abstract :
OLAP operations are used to process the data and gain useful information from it. These
information gives insight and detailed view. OLAP operations like roll up helps
summarize the data over a dimension (mostly useful if summarization done over time
dimension) and drill down operation can be used to present summarized data in more
detailed view. For our Data warehouse project we are going to using Company database
as a dataset to perform various operations on it such as roll up, drill down, Slicing, Dicing
and Scoping. We would be performing various OLAP operations on the dataset and gain
information like employees productivity over months with a roll up operation.
Data Mining Project
Title : Data mining on Consumer Complaints data set
Data set : Consumer Complaints Dataset
Objective :
The main objective of the data mining project is to use data mining tools and analyze the
data to discover information related to consumer complaints.
Abstract :
Data mining is used to gain knowledge and identify hidden patterns in the large datasets.
But for such huge amount of data there is always a need of better and powerful tools and
techniques. In our data mining project we are using consumer complaints dataset found
from the U.S. government website and we will be revealing complaints patterns and
company responses for those complaints, with the data mining tools. In that context, our
main idea is to use free and open sourced data mining softwares (tools), WEKA and
RapidMiner, to identify hidden patterns and compare the results and performances of
both tools. There are various classification and clustering algorithms available for doing
data mining within those tools. In this project we have selected one classification and one
clustering algorithm to perform in both tools and the project also presents the
performance evaluation of those algorithms and tools as well.