Giter Club home page Giter Club logo

powerbi_donations_case_study's Introduction

Donations Case Study

An Organisation receives donations from Different individuals and companies. The data below is provided to answer the questions that follow.

Table of Content.

Dashboard View

image

Click to Download pbix file

Dataset

Click the Table Name to view the tables.

Table Name: Donor
FirstName LastName Country DonorType DonorID
John Smith USA Individual 1
Jane Doe France Individual 2
Peter Parker Germany Individual 3
Bruce Wayne South Africa Individual 4
Bruce Banner Mexico Individual 5
Tony Stark USA Individual 6
Natasha Romanoff Russia Individual 7
Logan Howlett Canada Individual 8
Diana Prince Greece Individual 9
Guy Gardner Brazil Individual 10
Donald Blake Norway Individual 11
Clark Kent United States Individual 12
ABC Corp USA Corporation 13
MicroMax France Corporation 14
WidgetMakers LLC UAE Corporation 15
International Business Co Mexico Corporation 16
Fence Foundation United States Foundation 17
CA Trust Sweden Foundation 18
Benevolent Society United Kingdom Foundation 19
Charitable Giving, Inc. Saudi Arabia Foundation 20
Table Name: Donation
DonorName Amount GiftDate CampaignID GiftID
John Smith 5.25 1/1/2018 1 100
Jane Doe 175 2/2/2018 1 101
Peter Parker 340 3/6/2018 1 102
Bruce Wayne 123456 4/7/2018 2 103
Bruce Banner 725.15 5/9/2018 2 104
Anthony Stark 500000 6/10/2018 2 105
Natasha Romanoff 325 7/12/2018 6 106
Logan Howlett 15 8/13/2018 6 107
Diana Prince 50 9/14/2018 6 108
Guy Gardner 0.5 10/16/2018 1 109
Donald R Blake 150 11/17/2018 6 110
Clark Kent 100 12/19/2018 6 111
ABC Corp 1000 1/1/2018 4 112
MicroMax 5000 1/15/2018 4 113
WidgetMakers LLC 50000 2/2/2018 5 114
International Business Co 100000 3/6/2018 4 115
Fence Foundation 500 4/7/2018 5 116
CA Trust 20000 5/9/2018 4 117
Benevolent Society 100000 6/10/2018 5 118
Charitable Giving, Inc. 500000 7/12/2018 4 119
ABC Corp 1000 8/13/2018 9 120
Anthony Stark 1000000 9/14/2018 8 121
Benevolent Society 500 10/16/2018 4 122
Bruce Banner 1 11/17/2018 1 123
Bruce Wayne 5000 12/19/2018 8 124
CA Trust 500 1/20/2019 7 125
Charitable Giving, Inc. 7000 2/21/2019 7 126
Clark Kent 100 3/25/2019 1 127
Diana Prince 50 4/26/2019 1 128
Donald R Blake 75 5/28/2019 1 129
Fence Foundation 1500 6/29/2019 8 130
Guy Gardner 10 7/31/2019 1 131
International Business Co 75000 9/1/2019 7 132
Jane Doe 800 10/3/2019 1 133
John Smith 90 11/4/2019 1 134
Logan Howlett 50 12/6/2019 1 135
MicroMax 6500 1/7/2020 4 136
Natasha Romanoff 50 2/8/2020 1 137
Peter Parker 20 3/11/2020 1 138
WidgetMakers LLC 10000 4/12/2020 8 139
WidgetMakers LLC 20000 5/14/2020 3 140
Peter Parker 50 6/15/2020 1 141
Natasha Romanoff 40 7/17/2020 1 142
MicroMax 30000 8/18/2020 3 143
Logan Howlett 500 9/19/2020 7 144
John Smith 300 10/21/2020 6 145
Jane Doe 40 11/22/2020 7 146
International Business Co 40000 12/24/2020 3 147
Guy Gardner 50 11/22/2020 7 148
Fence Foundation 750000 10/21/2020 3 149
Donald R Blake 1500 9/19/2020 3 150
Diana Prince 300 8/18/2020 7 151
Clark Kent 500 7/17/2020 6 152
Charitable Giving, Inc. 40000 6/15/2020 3 153
CA Trust 1500000 5/14/2020 3 154
Bruce Wayne 10000000 4/12/2020 3 155
Bruce Banner 100 3/11/2020 6 156
Benevolent Society 500000 2/8/2020 3 157
Anthony Stark 10000000 1/7/2020 3 158
Table Name: Campaign
DonorName Amount GiftDate CampaignID GiftID
John Smith 5.25 1/1/2018 1 100
Jane Doe 175 2/2/2018 1 101
Peter Parker 340 3/6/2018 1 102
Bruce Wayne 123456 4/7/2018 2 103
Bruce Banner 725.15 5/9/2018 2 104
Anthony Stark 500000 6/10/2018 2 105
Natasha Romanoff 325 7/12/2018 6 106
Logan Howlett 15 8/13/2018 6 107
Diana Prince 50 9/14/2018 6 108
Guy Gardner 0.5 10/16/2018 1 109
Donald R Blake 150 11/17/2018 6 110
Clark Kent 100 12/19/2018 6 111
ABC Corp 1000 1/1/2018 4 112
MicroMax 5000 1/15/2018 4 113
WidgetMakers LLC 50000 2/2/2018 5 114
International Business Co 100000 3/6/2018 4 115
Fence Foundation 500 4/7/2018 5 116
CA Trust 20000 5/9/2018 4 117
Benevolent Society 100000 6/10/2018 5 118
Charitable Giving, Inc. 500000 7/12/2018 4 119
ABC Corp 1000 8/13/2018 9 120
Anthony Stark 1000000 9/14/2018 8 121
Benevolent Society 500 10/16/2018 4 122
Bruce Banner 1 11/17/2018 1 123
Bruce Wayne 5000 12/19/2018 8 124
CA Trust 500 1/20/2019 7 125
Charitable Giving, Inc. 7000 2/21/2019 7 126
Clark Kent 100 3/25/2019 1 127
Diana Prince 50 4/26/2019 1 128
Donald R Blake 75 5/28/2019 1 129
Fence Foundation 1500 6/29/2019 8 130
Guy Gardner 10 7/31/2019 1 131
International Business Co 75000 9/1/2019 7 132
Jane Doe 800 10/3/2019 1 133
John Smith 90 11/4/2019 1 134
Logan Howlett 50 12/6/2019 1 135
MicroMax 6500 1/7/2020 4 136
Natasha Romanoff 50 2/8/2020 1 137
Peter Parker 20 3/11/2020 1 138
WidgetMakers LLC 10000 4/12/2020 8 139
WidgetMakers LLC 20000 5/14/2020 3 140
Peter Parker 50 6/15/2020 1 141
Natasha Romanoff 40 7/17/2020 1 142
MicroMax 30000 8/18/2020 3 143
Logan Howlett 500 9/19/2020 7 144
John Smith 300 10/21/2020 6 145
Jane Doe 40 11/22/2020 7 146
International Business Co 40000 12/24/2020 3 147
Guy Gardner 50 11/22/2020 7 148
Fence Foundation 750000 10/21/2020 3 149
Donald R Blake 1500 9/19/2020 3 150
Diana Prince 300 8/18/2020 7 151
Clark Kent 500 7/17/2020 6 152
Charitable Giving, Inc. 40000 6/15/2020 3 153
CA Trust 1500000 5/14/2020 3 154
Bruce Wayne 10000000 4/12/2020 3 155
Bruce Banner 100 3/11/2020 6 156
Benevolent Society 500000 2/8/2020 3 157
Anthony Stark 10000000 1/7/2020 3 158

Relationships

To answer the questions I created relationships between the three tables using star schema model.

  • Fact Table: Donation
  • Dimentional Tables: Campaign & Donor

image

Questions

  1. How much money was raised month over month for the last three years, by department?
  2. What are the most successful campaigns year over year by Channel and Sub-Channel?
  3. Who are the top five Donors by DonorType for the latest year?
  4. What was the income raised month over month for the last three years by country?
  5. What percent of income was raised outside the US year over year?

Solution.

Q1) How much money was raised month over month for the last three years, by department?

Visual: matrix

Columns: Campaign.department

Rows: Donation.Amount, donation.gift date(Month)

image

Q2) What are the most successful campaigns year over year by Channel and Sub-Channel?

Visual: Slicer

Filters: donation.gift date(Year)

Select a filter to compare years

image

Q3) Who are the top five Donors by DonorType for the latest year?

Visual: Multi row card

DAX calculation:

Top5Donors = 
TOPN(5 , Donation, [Amount] )

image

Q4) What was the income raised month over month for the last three years by country?

Visual: Matrix Columns: Donor.country, Rows: donation.amount, donation.gift date(Month)

image

Q5) What total income was raised outside the US year over year?

Visual: Card

DAX calculation:

OutsidetheUSA = 
CALCULATE(SUM(Donation[Amount]), Donor[Country] <> "United States")

image

powerbi_donations_case_study's People

Contributors

mukaruernest avatar

Stargazers

 avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.