Business Intelligence and Data Visualization: Crowd Funding and Great Eastern University Analysis

Business Intelligence and Data Visualization
Assignment 2

Table of Contents
Abstract................................................................................................................................3
Part I. Crowd Funding.......................................................................................................4
a. Introduction....................................................................................................................5
b. Variables.........................................................................................................................4
c. Graphical Analysis.........................................................................................................5
d. Statistical Analysis.........................................................................................................3
e. Results and Conclusions.................................................................................................3
Part II. Great Eastern University.....................................................................................4
a. Benefits of Statistical Data analysis using different Software’s......................................5
b. Advantages of using advanced data analytics tool at Great Eastern University..............4
c. Process of Using Analytic tools at Great Eastern University..........................................4
d. Meaning of quote by Ken Rudin.....................................................................................4
e. Implementation of Ken’s suggestion at Great Eastern University..................................4
References............................................................................................................................5
Appendix..............................................................................................................................5
2 | P a g e

Assignment 2
Business Intelligence and Data Visualization
Abstract
Data analysis for the crowd funding data set was performed by using different statistical
software’s. It is observed that duration for most of the project is given as 30 days. It is observed
that the frequency for the less project update count is more and as the project update counts are
increasing the frequency is decreasing. It is observed that the major categories used by the people
for their projects are music, film and video, publishing, and arts. It is observed that most of the
projects have their own facebook pages. It is observed that about 14368 projects are categorized
as failed, while about 14079 projects are categorized as success. Average number of days for
completion of projects is given as 32.75 days with the standard deviation of 10.98 days. There is
sufficient evidence to conclude that there is a statistically significant difference exists between
the average goal amounts for the different duration periods in days. There is sufficient evidence
to conclude that the average number of count of pledges for failed projects and succeed projects
is not same.
Part I
Crowd Funding
a. Introduction
Business intelligence and Data visualization are the most important scenarios in
today’s world of businesses. Data visualization consists of the different techniques for
exploration of the data by using different tools and techniques of statistical analysis.
Here, we have to analyse the data set related to the fund collection for different types
of projects. For the analysis of this fund data set, we have to use different statistical
tools and techniques. After analysis of this fund data set, we have to find the facts that
would be helpful for obtain money via crowd funding to fund a creative project. We
will get advices for success of project and we will get general idea about the crowd
funding for creation of different projects. This data analysis work will be useful for
the people who want to create similar crowd funding projects. In terms of project
succeeds, we have to find out the most important and significant attributes for crowd
3 | P a g e

funding data set. We will use the software’s like BigML and SPSS for the analysis of
the given data sets. For the statistical analysis of the given data set, we will use basic
descriptive statistics, graphical analysis, and inferential statistical analysis by using
SPSS and other software’s. Let us see this research study in detail.
b. Variables
For this research study, we have to analyse the crowd funding data set by using
different statistical software’s. Data for this research study is downloaded from the
blackboard. The data set PleaseFundThis.xlsx have many variables such as project
name, date launched, duration days, goal $, percent raised, project state, amount
pledged $, major category, minor category, etc. The list of all variables with scale of
variables is summarised as below:
No. Variable Scale
1 project_name Nominal
2 date_launched Nominal
3 duration_days Ratio
4 goal_$ Ratio
5 percent_raised Ratio
6 project_state Nominal
7 amt_pledged_$ Ratio
8 major_category Nominal
9 minor_category Nominal
10 project_updated_count Ratio
11 city Nominal
12 region Nominal
13 number_of_pledgers Ratio
14 comments_count Ratio
15 avg_amt$_per_pledger Ratio
16 project_has_video Nominal
17 project_has_facebook_page Nominal
18 facebook_friends_count Ratio
19 project_has_pledge_rewards Nominal
20 lowest_pledge_level_$ Ratio
21 highest_pledge_level_$ Ratio
22 total_count_of_pledge_levels Ratio
23 success Nominal
4 | P a g e