Data Nectar worked with the state university to restructure the legacy database architecture to high-performance modern architecture.
With 70 odd databases in scope, the challenging scale of operation involved data model refactoring, data extraction, data quality improvements, migration, and loading into a unified database capable of serving the Admin applications as well as the data analytics & reporting needs.
The solution enabled the university in delivering administration services better, and faster, while reducing operational costs.
Reduced cost of database
Reduction in DBA team size
Reduction in time to service student’s
A leader in the higher education industry operating more than 480 colleges under its University that offers 600+ courses and boasts of more than 400,000 enrolled students. The educational institution had disparate databases for managing more than 2 million students records from 2007 to 2018 separated across semesters. It was highly time-consuming and complex to manage, carry out data transfer from one database to another as the student progresses up their academic tenure. Generating specific reports or making any sort of analytical process was heavily bottlenecked heavily.
The university has 4 systems to separately process student’s information pertaining to a specific academic semester.
- Student and admission portal
- Enrolment process system
- Examination system
- Degree awarding system
University operating more than 480 colleges | 600 courses | 40,00,000 students enrolled
- Database design & development
- Data migration to unified database
- Enterprise grade ETL
- Reports & Dashboards
- Training & Support
Considering there was no access to consolidated data of any student through a single solution, the institution currently had to execute extensive manual work to prepare a consolidated academic report for any student. It involved querying numerous databases and demanded a lot of interdepartmental coordination. Besides that, high dependencies on staff having strong know-how of data structures and queries were posing challenges to deliver results on time.
The redundant processes made it extremely difficult for current and historic records and information about student’s academic performance to be made available to data analysts and decision-makers. Also, significant time was taken to serve requests for a varying range of academic records, certifications, transcripts, and many more. Self-service BI reports were not possible for concerned stakeholders and had to be dependent on staff’s availability & skills for generating specific analytical reports.
Designing high-performance database architecture and development of consolidated, normalised and scalable database was core to address the challenges.
- Inconsistent designs of 70+ databases
- Data validation & quality management for migration between systems every 6 months
- Heavy lifting manual work and dependencies on analysts to prepare reports and extract insights
- Multiple points of error
Implemented ‘ENROLL to EXAMINATION’ system that involves yearly transfer of student records to other systems as they progress during their academics.
After making a comprehensive assessment of the current system bottlenecks, data migration, and data analytics processes, Data Nectar Technosys designed a new database consisting of efficient data models and a scalable ETL solution to transform the redundant processes in the current setup to a high-performing unified database solution.
This involved the design and development of a single normalised database, heavy data migration, cleansing, and transformation of the academic details of more than 2 million studentsthroughout their education tenure. Also, Dashboards and Self-service BI reporting systems were built on top of the OLAP Cubes for faster data delivery to Dashboard for various stakeholders. Besides, customised training for technical and non-technical staff was delivered.
Cost reduction for Database management
Reduction in time to service
student requests for various academic
records (from 4 Hrs to 1 Hr)
Reduction in team of DBA and Analysts earlier required for manual data migration efforts every six months
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