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This project aims to organize and analyze SURE Trust's student data using Python, Google Data Studio, and Sheets. We're uncovering enrollment patterns, demographics, and enrollment influencers through data cleaning and visualization to enhance SURE Trust's student management and experience.

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Unlocking-Insights-SURE-Trust-Comprehensive-Student-Data-Analytics

This project aims to organize and analyze SURE Trust's student data using Python, Google Data Studio, and Sheets. We're uncovering enrollment patterns, demographics, and enrollment influencers through data cleaning and visualization to enhance SURE Trust's student management and experience.

Domain of the project : Data Science and Data Analytics

Mentors

  1. Sravan Nemana
  2. Harshee Pitroda

Team Members

1.Mr.Bhargavesh   B.Tech, 4th year pursuing - Team Leader
2.Ms.K R Sindhu   B.Tech, 4th year pursuing - Team member
3.Ms.C.Ramyasree  B.Tech  4th Year pursuing - Team member
4.Ms.U.Sravani    B.Tech  4th Year pursuing - Team member
5.Ms.Harini       B.Tech  4th Year pursuing - Team member
6.Ms.T.Rahithya   B.Tech  4th Year pursuing - Team member

Period of the project

April 2023 to August 2023

Table of contents

  1. Executive summary

  2. Introduction

  3. Project Objectives

  4. Methodology & Results

  5. Social / Industry relevance of the project

  6. Learning & Reflection

  7. Future Scope & Conclusion

Executive summary

Sure Trust is a notable organization dedicated to offering free courses to rural people, facilitated by top-tier trainers. Given the widespread nature of enrollments from various regions across the country, a comprehensive analysis of Sure Trust's enrollment data becomes imperative. This analysis holds the key to enhancing the organization's services and operational efficiency. The challenge lies in effectively utilising the enrollment data to uncover valuable insights.

By closely examining enrollment data, Sure Trust can gain invaluable insights into enrollment patterns, course preferences, and participant demographics. This data-driven approach will enable the organization to tailor its offerings more effectively, ensuring that the courses provided align precisely with the needs and aspirations of the rural learners. Ultimately, this analysis will not only elevate the operational quality of Sure Trust but also contribute significantly to the overall betterment of the organization's functionality and impact on rural education.

Introduction

Data Science:

Data science is a multidisciplinary field that involves extracting insights, knowledge, and meaningful information from large and complex datasets. It combines elements of statistics, computer science, domain expertise, and data visualisation to uncover patterns, trends, and correlations within data. The ultimate goal of data science is to make informed decisions and predictions based on the analysis of data. Key components of Data Science includes:

  • Data collection
  • Data cleaning
  • Exploratory Data Analysis (EDA)
  • Data preparation
  • Iterative Process
  • Interpretation and Communication Data science has become immensely important in today's world due to its transformative impact on various industries and sectors.Important decision making, predictive analysis,risk management, customer insights these are the few key reasons highlighting the importance of data science. Its importance will only continue to grow as technology advances and the volume of data generated increases exponentially.

Problem statement / Goals of the project:

Sure Trust, committed to providing free courses to rural communities, has experienced widespread enrollments from various regions across the country. In light of this extensive participation, there arises a critical need for a comprehensive analysis of Sure Trust's enrollment data.The primary problem is how to decipher this data in a way that enables Sure Trust to refine its offerings precisely according to the unique needs and aspirations of the students. By analysing its enrollment data to gain actionable insights that will enable the organisation to optimise its course offerings, enhance operational efficiency, and amplify its positive influence on rural education and empowerment.

About the dataset:

SURE Trust enrollment data consists of 13 columns and 7033 rows.This data includes name of the student, gender, phone number, qualification of the student, college name, college place, college state, college district and also it includes when that particular enrollment was done including month, day, hour, minutes and seconds.

Data Cleaning:

Data cleaning is a crucial step in the data preparation process. It involves identifying and rectifying errors, inconsistencies and anomalies within a dataset to ensure that the data is accurate, reliable, and suitable for analysis. The quality of data directly impacts the effectiveness and validity of any data analysis, modelling, or decision-making process.

Project Objectives

Enrollments Prediction by State: Determine which states are likely to experience higher enrollment rates for Sure Trust courses. Enrollment Hotspots by District and Location: Identify the specific districts and geographical locations within each state where enrollments for Sure Trust courses are concentrated. College Enrollment Analysis: Analyse the enrollment data to pinpoint colleges or educational institutions that have a higher number of Sure Trust course enrollments. Course-Specific Enrollment Analysis: Evaluate the enrollment data to discover which particular courses offered by Sure Trust attract the most enrollments. Qualification-Based Enrollment Study: Examine the data to understand which specific qualifications or educational backgrounds are most prevalent among the enrolled students. Time-of-Day Enrollment Trends: Investigate enrollment data to pinpoint the times of day when Sure Trust courses receive the most enrollments. Day-of-the-Month Enrollment Trends: Analyse enrollment data to discover which days within a month witness higher enrollments for Sure Trust courses. These objectives aim to guide the comprehensive analysis of enrollment data for Sure Trust, enabling targeted improvements and better alignment with the needs of students in various regions and backgrounds.

Expected outcomes and deliverables.

Data-Driven Insights: A wealth of data-driven insights that provide a clear understanding of enrollment patterns, preferences, and trends among students from rural communities. Enrollment Data Analysis Report: A comprehensive report detailing enrollment trends, regional distributions, and demographic insights. Expansion Roadmap: A roadmap for expanding Sure Trust's offerings to regions and colleges with high potential for impact. Helpful for performance development of the organisation in a positive way and can extend its service for a wide range of students. Customization Recommendations: Recommendations for course customization, content enhancement, and recommending courses which are having high demand and importance. These expected outcomes and deliverables will empower Sure Trust to make informed decisions, refine its approach, and ensure that its free courses effectively serve the unique needs of rural communities across the country.

Methodology and Results

Methods/Technology used:

Tools/Software used:

Google Looker Studio: Looker Studio might refer to a part of the Looker platform that's focused on data visualisation and dashboard creation. Looker Studio provides a user-friendly interface for designing and customising interactive dashboards and reports. Users can drag and drop visual elements, charts, and widgets onto the canvas to create compelling data visualisations without needing extensive coding knowledge. Looker Studio aims to make the process of creating data-driven visuals more accessible to users who might not be deeply technical. Looker Studio provides features for data governance and control. Organisations can ensure that the right users have access to the right data while maintaining security and compliance. Looker Studio supports collaboration by allowing users to share dashboards, reports, and insights with team members. This facilitates better communication and alignment across departments.Looker Studio can connect to multiple data sources and create a centralised repository for data analysis. This reduces the need for manual data extraction and manipulation.

Spreadsheets: Google Sheets is a cloud-based application, which means you can access your spreadsheets from any device with an internet connection. This makes it easy to work on your spreadsheets from different locations and collaborate with others in real-time.Collaborative Editing: One of the standout features of Google Sheets is its real-time collaborative editing. Multiple users can work on the same spreadsheet simultaneously, and changes are automatically saved and synced for all users. You can also leave comments and suggestions. Google Sheets includes a wide range of functions and formulas that allow you to perform complex calculations and data analysis. It supports most Excel functions.You can control who has access to your Google Sheets and what level of access they have (view, edit, comment).

Python : Python is a high-level, general-purpose, and very popular programming language. Python programming language (latest Python 3) is being used in web development, Machine Learning applications, along with all cutting-edge technology in Software Industry. Python language is being used by almost all tech-giant companies like – Google, Amazon, Facebook, Instagram, Dropbox, Uber… etc.

Data collection approach:

The data gathering method consisted of retrieving three years' worth of enrollment data from SURE Trust and saving it in a CSV file format.

Project Architecture:

- Data Collection and Integration
- Data Storage
- Data Processing and Analysis
- Data Visualization and Reporting
- Continuous Improvement
- Security and Compliance

Outputs

OutputVideo.mp4

Output Mobile view

Output

1.Highest enrollments from which college

Output

According to the provided visual, RGUKT College has the highest enrollment, with a total of 1055 students, followed by MITS College, which has 625 enrollments.

2.Enrollments based on qualification

Output

The visual representation indicates that the enrollment numbers for B.Tech courses are significantly higher compared to other qualification levels. SURE Trust offers courses for B.Tech, undergraduate degrees, MBA, M.Sc., and M.Com.

3.District wise count of students

Output

The map illustrates student enrollments from various districts across the country, with different colours representing different districts. As the enrollment count increases, the size of the circle representing each district also increases. Notably, Kadapa stands out with the highest number of enrollments.

Output

The data is presented in a tabular format, and it's worth noting that SureTrust is offering its services in a remarkable total of 149 districts, marking a significant achievement.

4.Count of enrollments in a day,month and year

Output

The visual representation displays enrollment data categorised by specific day, month, and year. It's evident that there is a noticeable increase in enrollments during the month of October 2022.

5.Hour wise enrollments

Output

The line chart above illustrates the times of the day when students are enrolling for courses, with different colours representing different months. Notably, there is a consistent trend of high enrollment numbers during the afternoon, and it's also noteworthy that enrollments occur around the clock, with 24-hour availability.

6.Month wise enrollments

Output

The line chart presents a month-wise breakdown of enrollments, with November standing out as the month with the highest number of enrollments, while September has the lowest enrollments.

7.Stream wise count of enrollments

Output

The enrollment data is categorised by streams, with a significant majority of students opting for B.Tech programs. Notably, Mechanical Engineering accounts for more than 100 students. It's worth mentioning that SureTrust offers courses across nearly 10 different streams of study.

Social / Industry relevance of the project

The project's social and industry relevance lies in its ability to improve educational access and quality, empower rural communities, bridge education gaps, promote data-driven decision-making, and serve as a model for scalable and sustainable education initiatives. It underscores the importance of tailoring educational offerings to meet the specific needs and aspirations of underserved populations, ultimately contributing to broader social and economic development.

Learning & Reflection

Learning and Experience: Through the course of the project, I gained a diverse skill set encompassing various aspects of Data Analytics. This hands-on experience in these technical domains broadened my technical proficiency and reinforced my ability to tackle complex challenges. On the management front, leading the team provided me with invaluable insights into project coordination, task allocation, and effective communication. Conducting weekly standup meetings and addressing doubts nurtured my leadership and communication skills, allowing me to guide the team toward a cohesive and productive workflow. My journey as a team lead and developer was both transformative and enriching. Collaborating with the team to implement intricate technical features. Navigating the role of a team lead deepened my understanding of project management and leadership dynamics. Overcoming challenges and celebrating milestones together with the team created a sense of accomplishment that continues to inspire my future endeavors.

Learning and Experience: Engaging in a real-time Data Science project using student data was a transformative experience for me. It has provided an invaluable opportunity to apply theoretical knowledge to practical scenarios , deepening my understanding of data analytics techniques and tools. I had the opportunity to work with substantial datasets in real time, which greatly improved my skills in data preprocessing, visualisation, and statistical analysis. Furthermore, collaborating with a diverse team not only expanded my technical skills but also enhanced my communication and problem-solving skills.

Learning and Experience: Working in a real-time Data Science project with student enrollment data was really a very great experience for me. I got to handle large datasets in real-time, which improved my ability to efficiently prepare, present, and interpret the data. I have improved my knowledge in data visualisation and statistical analysis. I've become better at managing my time because I've learned how to handle both my academics and this project effectively. Working in a team enhanced my team management and communication skills.

Learning and Experience: Through this real-time Data Science project titled “SURE Trust’s Comprehensive Student Data Analytics”, gained knowledge on how to arrange and utilise raw data for creating a dynamic dashboard and received practical expertise with robust technologies like Python, Google Looker Studio, and Google Sheets. Also I had come across preparation of documents and giving presentations about this project in our SURE Trust's LST sessions.Preparing KPIs and visuals for this project was always a fun way to gain knowledge. Constant support from my team helped me become a strong team player and improved my communication skills.

Learning and Experience: This real-time data analytics project with students enrollments data has been an impactful educational experience.It provided an invaluable opportunity for deepening my understanding of data analytics techniques and tools which includes google looker studio and spreadsheets.I had the chance to work with dataset in real-life situations,which greatly enhanced my proficiency in data preprocessing, data visualisation and analysis.Engaging with my teammates and mentors creates an environment for sharing knowledge and benefiting from each other's experiences, skills and expertise. I view this as a fantastic opportunity for skill enhancement.

Name: K.Harini

Learning and Experience: During my involvement in the real-time Data Science project titled "SURE Trust's Comprehensive Student Data Analytics," I acquired valuable knowledge on how to organise and effectively utilise raw data to create a dynamic dashboard. Additionally, I gained practical expertise in using robust technologies such as Python, Google Looker Studio, and Google Sheets. Within the context of our SURE Trust's LST sessions, I became proficient in preparing documents and delivering presentations about this project. Crafting KPIs and visuals for this endeavour was consistently enjoyable and contributed significantly to my knowledge acquisition. My team's unwavering support played a pivotal role in fostering my growth as a strong team player and enhancing my communication skills.

Conclusion and Future Scope

In conclusion, the comprehensive analysis of Sure Trust's enrollment data is crucial in its commitment to providing free courses to rural communities. This project has successfully addressed the primary problem of deciphering data to refine offerings according to the unique needs and aspirations of the students. Key findings and recommendations have been identified to guide Sure Trust in its mission to better serve its diverse student population.

Throughout the project, several key findings have emerged such as Course Effectiveness: Data analysis has revealed which courses are more popular and effective among students, enabling Sure Trust to allocate resources more efficiently.Regional Variations: Geographic analysis has highlighted regional variations in enrollment, allowing for targeted efforts to address underrepresented areas.

The future scope of the project to decipher Sure Trust's enrollment data and refine its offerings precisely according to the unique needs and aspirations of the students should focus on continuous improvement and adaptation to changing circumstances. By considering these insights, key findings and recommendations, Sure Trust can continue to evolve and fulfil its mission of providing quality education to rural communities, precisely tailored to their unique needs and aspirations. This ongoing commitment will contribute to the empowerment and development of the organisation, ultimately creating a brighter future for all involved.By continuously evolving and innovating, Sure Trust can make a lasting impact on the educational landscape of rural areas across the country.

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This project aims to organize and analyze SURE Trust's student data using Python, Google Data Studio, and Sheets. We're uncovering enrollment patterns, demographics, and enrollment influencers through data cleaning and visualization to enhance SURE Trust's student management and experience.

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