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https://github.com/jamesehiabhi/grace-edtech-hub

Analysis Report on Grace EdTech Performance Database
https://github.com/jamesehiabhi/grace-edtech-hub

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Analysis Report on Grace EdTech Performance Database

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README 

        
# Grace EdTech Hub

## Analysis Report on Grace EdTech Performance Database



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### Introduction



The Grace EdTech database provides a structured framework for managing educational data, including course details, teacher records, student scores, and salary information. This report presents an analytical overview of the dataset, showcasing key insights into academic performance, faculty composition, and salary distribution.



### ✨Course Analysis and Popularity



This categorization helps in understanding student preferences and the popularity of different courses, which can inform curriculum planning and resource allocation, including course structures that help in evaluating the academic rigour and credit load assigned to each course. Courses were categorized based on the number of students who have taken them:



-   **Popular**: More than 5 students

-   **Moderate**: 3 to 5 students

-   **Unpopular**: Fewer than 3 students



This information is essential for curriculum planning and workload balancing.



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### ✨Teacher Demographics



A focused analysis of faculty demographics was conducted by filtering the dataset for female teachers. This reveals the gender distribution among the teaching staff. The database query extracted:

- Teacher Name

- Gender



Such insights can inform diversity policies and hiring strategies within the institution.



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### ✨Student Performance Trends



Student scores provide critical insights into academic achievement. Several queries were conducted:

1.	Listing students who scored above 80 in any course.

2.	Identifying students who scored above 70 specifically in the EX103 course.



These analyses help assess student proficiency and highlight potential areas where academic interventions may be required.



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### ✨Faculty Compensation Analysis



To understand salary distribution, a query was executed to determine the highest salary among all teachers. By retrieving:

- Teacher Name

- Salary



This information provides insights into salary competitiveness and compensation structure.



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👉 **_Further Analyses were conducted on the system to provide more overview of the academic landscape at_** [Grace EdTech SQL](https://github.com/jamesehiabhi/EdTech-Academy-Hub/blob/main/Grace%20EdTech%20SQL.sql)



    Course-Specific Performance

    Course Offerings and Units

    Average Course Scores

    Above Average Performers

    Department with Most Courses

    Top Scoring Student across all courses

    Textual Score Representation

    Department ID Transformation

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### Conclusion

The Grace EdTech database is a valuable resource that enhances academic and administrative decision-making. By utilizing this comprehensive dataset, institutions can optimize curriculum design, monitor student performance, and assess salary competitiveness. Further exploration could reveal additional strategic recommendations for continuous improvement. These insights provide a detailed overview of the academic landscape at Grace EdTech, highlighting strengths and opportunities for enhancement. This report is essential for strategic planning, academic support, and improving the overall educational experience.

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### *Kindly share your feedback and I am happy to Connect 🌟*



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