/ Case Study · Education

A Law School Turns Raw Data Into Clear Decisions. Power BI on a Clean Warehouse.

/ The engagement

A BI Reporting Solution Built on MS-SQL.

The client is a leading United States law school with around 100 faculty members and 3,000 students, known for graduates who pass the demanding California Bar. Its data sat in an MS-Access database with no data dictionary. Brainvire migrated it to MS-SQL, built a data warehouse and a data dictionary, and delivered a Power BI reporting solution with dashboards, sub-reports up to 30 pages, and on-demand report generation.

MS-SQL MigrationData WarehousePower BI DashboardsAutomated Reports

3,000Students analyzed

100Faculty members

30 PagesComparison reports

On-DemandReport generation

/ About the client

US Law School

With around 100 faculty members and 3,000 students, the client is a leading United States law school known for producing graduates who pass the difficult California Bar. It holds high standards of research and scholarship and needed to turn its data into decisions, but the existing MS-Access database had no data dictionary or reference document.

Migrating to MS-SQL was a monumental task that required careful study of object relationships and the removal of redundancies. Once the data dictionary was built, Brainvire implemented its BI Reporting Solution, creating a data warehouse, a set of dashboards for key performance indicators, and an automated system that generates up-to-date reports on demand.

/ The approach

Design, architecture, and features, shipped as one program.

/01Faculty

Analyzed with data mining

Student and faculty data was large and slow to work with, so the team used data mining and clustering to uncover patterns and relationships across faculty performance.

/02Dashboards

Built to requirement

The client needed a tailored view, so the team built a custom dashboard with filters and slicers for acceptance rate, tuition cost, student-faculty ratio, and bar passage analysis.

/03Sources

Combined into one table

Data arrived unstructured from many sources, so the team used Query Editor and Merge Queries to combine it into one clean table for reporting.

/04Migration

Restructured to MS-SQL

The database needed a rebuild, so the team restructured the schema, migrated from MS-Access and third-party tools to MS-SQL, and added sub-reports up to 30 pages exportable to Excel.

/ What stood in the way

Four problems, solved without a maintenance window.

Select a challenge to see how it shaped the build.

/01 Integrating faculty performance analysis →

/02 A custom dashboard →

/03 Accessing data from different sources →

/04 Restructuring the database →

Integrating faculty performance analysis

The team had to work with a huge volume of student and faculty data that was slow to process. It applied data mining and machine learning, using clustering to group similar data points and identify relationships between them.

A custom dashboard

The client needed a custom dashboard built to its business requirements. The team added filters and slicers and delivered a dashboard covering acceptance rate, tuition cost, student-faculty ratio, and bar passage analysis, integrated with existing systems.

Accessing data from different sources

Data was fetched from many sources and was completely unstructured. The team used Query Editor to combine sources into one table and the Merge Queries feature to join tables from different sources.

Restructuring the database

The project required database migration and third-party tool integration. The team restructured the schema, migrated data from MS-Access and other software to MS-SQL, and added a sub-reporting feature of up to 30 pages exportable to Excel.

/ Product screens