In this project, we built a three-page Tableau dashboard with key metrics and visualizations to track student engagement with the 365 Data Science platform from January 1 to October 20, 2022.
We retrieved data from the 365 Data Science database using MySQL, which includes real-life records on students, purchases, and courses. Finally, we answered key questions to help the company better understand customer registration, engagement, and demographic patterns. This helps refine marketing strategies, tailor course offerings, and boost user retention, ultimately driving business growth.
We designed queries to extract data from 365 User Database.sql and stored them in three files:
1. Courses Information.sql2. Purchases Information.sql3. Students Information.sql
Finally, we exported the retrieved data to CSV files with matching names and imported them into Tableau.
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We created a course engagement table showing the top
8courses by total minutes watched, along with average minutes watched, total ratings, and average rating. -
We made two horizontal bar plots: one for the top
8countries by total students and another for the top8countries by total minutes watched. Filtering was based on registration month (January to October2022) and subscription type (All, Free, Paid). -
We created a bar plot with a line for total and average minutes watched, filtered by subscription type (All, Free, Paid). We also created a bar plot showing the percentage of onboarded vs non-onboarded students by month with no filtering.
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Finally, we calculated key performance indicators (KPIs) for total students registered, total minutes watched, average minutes watched, and the percentage of students onboarded. For the first three metrics, filtering was done based on start date, end date, and subscription type.
1. How many students registered for 365 Data Science during our analysis period? What’s the total percentage of onboarded students? How does the monthly onboarding rate fluctuate?
The KPI for total students registered shows 35,230 students registered on the platform during the analysis period. The percentage of onboarded students is 51.54%, meaning just over half of the registered students engaged with the platform.
Why didn't around half of the students watch any content? This could be due to user experience issues, difficulty finding interesting content, or not knowing where to start. To address this, we suggest:
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Testing the platform for potential issues.
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Following up with users who didn’t watch any content to understand their experience, and possibly adding missing content if needed.
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Enhancing the user journey by guiding them to a structured learning path with rich data projects.
The monthly onboarding rate fluctuates between 46.29% and 64.54%, with the highest rate of 64.54% in October. However, our data didn’t include the last 11 days of October in the analysis.
The most watched course is "Introduction to Data and Data Science," with 333,265.90 total minutes watched. This is expected, as it’s an introductory course and a common starting point for students. With around 2 hours of content, it was watched for an average of 39.09 minutes and has an impressive average rating of 4.86 from 572 total ratings.
"SQL" is the second most watched course, with 234,824.80 total minutes watched. On average, students watched 144.60 minutes of this course, which has 11 hours of content. SQL is a key skill for anyone pursuing a career in data science or data analysis.
Other highly watched courses include "Statistics," "Introduction to Excel," and "Python Programmer Bootcamp." The average ratings for these five courses range from 4.78 to 4.86, reflecting excellent feedback given the high number of total ratings (between 101 and 572).
3. How do the total and average minutes watched change based on whether a student paid for a subscription?
During the entire analysis period, free-plan students watched a total of 490,762 minutes, while paying students watched 1,344,826 minutes. This significant difference is expected, as free-plan students generally have less motivation to study, and their content access is limited to 30 minutes per course. In contrast, paying students are more committed, seeking better value for their investment, and can access all content.
The difference in average minutes watched is also notable. Free-plan students watch an average of 28.96 minutes, while paying students watch about 669.4 minutes on average.
An interesting spike occurs between August 15 and 18, when free-plan students' average minutes watched increases to 73.8 minutes. This is due to 365 Data Science offering free access to all its students during this period, which boosted engagement.
4. Did the students spend more time watching courses as months passed? Did their watch time vary seasonally?
We observed a significant peak in total minutes watched by free-plan students in August, which resulted from the Free-Days campaign run by the 365 Data Science marketing team. However, this increase did not affect paying students, as they already had full access to the platform and weren't impacted by the campaign.
In general, students spent more time watching courses from June to October. It's important to note that October's data only includes 20 days, as the last 11 days were not part of the analysis.
5. Which countries have the most students registered based on their subscription type? Does this number scale proportionally with the total minutes watched per country?
Between January 1 and October 20, 2022, the countries with the most free-plan students are India (6,864), the USA (4,313), and Egypt (2,990). For paying students, the USA leads (679), followed by India, the UK, and Canada.
While there is a positive correlation between the total number of students and total minutes watched per country, the numbers do not always scale proportionally.