Louise’s play Fever is near to its fundraising goal in a less amount of time. She like to have an analysis of the different campaigns fared in respect to their launch dates and their funding goals.
This project is about using the data that been gathered and analysing-visualizing the campaign outcome. The key factors that we used to analyze the events are based on their launch dates and funding goals.
Initially, as Excel is one of the best tools in the market for doing analysis, to learn its features was little time consuming and challanging. However, once got familiar with the drill it was progressive. We have to understand,why we are taking the few data as the reference and how it makes an impact on the results. With proper study allocation time and thoroughly going data helps a lot in overcoming the challenge and at the end things were understandable and results were on expectations.
The pivot tables are been great assets to analyze this outcome based on the Launch Date. We have taken the data of launch dates in respect for outcome to the Successful, failed and canceled event. We have converted the launched date in Date created conversion then have the years data fetched out from it. The pivot chart based on the filters as parent category and years, which pin points the required data in respect to a particular selection. Columns and rows are divided among outcomes and Date created conversions respectively. The values in the chart go in terms of the count of outcomes.
The Graph contains the lines scaled in terms of the months and no of the events categorized in the three categories, Successful, Failed and Canceled events. From the graph it is been deducted that the Success ratio of the event is been more throughout the year, especially in between the month May and June. On average the number of the events for the Successful events stays above 60, there is a gradual rise from March till June then started to go down from June till Dec. The failed event ratio is been in between 25 to 55 throughout the year. The graph doesn’t vary much compare to the successful. The Cancelled events are been very low during the whole year. It stayed below 10 throughout the year. Overall, the event is successful. The total number of the successful events exceeds to failed events by 346 which lead to the successful outcome of the whole event.
The line graph is used to analyze the outcome based on the goals. The data from the successful, failed and canceled is distributed among the ranges of the goals amounts. It is divided among the following sections:
Goal
Number Successful
Number Failed
Number Canceled
Total Projects
Percentage Successful
Percentage Failed
Percentage Canceled
The individual total of ranges is been taken after that the percentage of successful, failed and canceled events are taken. The graph is taken in respect to the goal amount in the X-axis and percentage of the successful, failed and canceled events are taken on the Y-axis.
The blue line on the graph represents the percentage of successful events and orange line represents the percentage of the failed events. The successful event percentage curve is gradually decreasing as we go from the zero to 25000 goal budgets, after that the ratio of the event of getting successful kept increasing till the 35000 and remains steady for goal budget in between 35000 to 400000. A sudden decline in the percentage of the curve is seen after the range of 40000 till 49999 and inclined afterwards. The percentage of the failed events increases gradually from lowest goal budget till 25000. Afterwards it declines from 25000 to 35000 and remains steady till 40000. A sudden jump is been observe from 40000 till 45000 and gets decline afterwards till the highest budget.
There are challenges in learning anything new and challenges shows the progress. This project taught and refreshed my excel skill. The challenges that I faced during this project are:
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Filtering the pivot charts inorder to get the right data displayed on chart.
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Applying the formulas and double check the results by filtering the results. The above-mentioned points were tedious and little challenging as took a back-and-forth approach.
What are two conclusions you can draw about the Outcomes based on Launch Date?
- The number of Successful events is greater than the number of the failed events which makes the overall project successful.
- The month May has highest number of events occurred.
What can you conclude about the Outcomes based on Goals?
- The number of the canceled events are very low that it doesn’t affect the overall outcome.
- At range from 450000 to 44999 the failed percentage hit the maximum and successful percentage is minimum.
What are some limitations of this dataset?
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The amounts are in dollars however when it comes to currency conversion it limits the data at this point.
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The reason of making the events successful / failed / canceled is not mentioned and limits the ability to analyze the reason behind them. What are some other possible tables and/or graphs that we could create?
The possible tables:
The pledged column can be used instead of the goal column. Also, Can filter according the country data as well.The possible graphs:
The column chart, Pie, Bar, Box & Whisker etc. can be done as graphical representation.