Analyze the Excel sample project data and try to uncover market trends
This project referring to Module 1 is developed on an Excel software base related to the Bootcamp Data Analytics from the University of Toronto. The goal correspond of analyzing the data with a numerous of crowdfunding projects. All material regarding the findings and data analysis related to this project will be available on Github for public view.
For this project, students from Data Analytics need to apply all concepts that we have learned in class, including the main advanced Excel formulas such as conditional formatting, Countifs, PivotTable, Charts. Also, statistical modelling functions such as mean, Median, Standard Deviation, Min, Max in order to figure out highlights, trends and findings that support the business decision and stakeholders' needs.
An overview of the crowdfunding campaigns based on the dataset analyzed shows that the 57% of the projects has been successful in comparation to 36% that has failed. The Theatre category is a highlight that corroborates with the results specially during the year range from 2014 to 2016 and the month range between November and January.
The analysis by category showed that categories such as Theater, Music, Technology and Film & video, we find that all these are successful representing 81% of all successful outcomes categories.
When analyzed the outcome based on goals by category and specifically the category plays the first finding is 38% has failed which is a significant percentage for a unique category on the other hand the percentage of successful is 54% and only 7% were canceled.
The main limitation found during the development project was the deadline and some specific features used on excel for instance the countifs, pivot table and formatting if not applied correctly it can compromise the accuracy of the data, perhaps using an advanced formula called STOCKHISTORY would be relevant.
We could create a table using filter by subcategories, by all by year and just for successful outcomes, and sorting by most significant to smallest. Relate to graphs; It will be very visual using the Area Chart because it shows the participation in successful outcomes of each category by area visually which can be extremely important to define to the business to analyze performance and considerations in order to make the best evaluation for future campaigns.