Alahu Solutions Product

Turn Institutional Data Into Intelligence.

The Alahu Institutional Intelligence Platform gives colleges and universities one secure environment to ingest spreadsheets, understand their structure, identify reliable records, cross-match datasets, compare changes over time, and transform disconnected information into interactive dashboards and decision-ready reports.

Request a Product Demo Explore the Platform
CSV + Excel Dynamic ingestion
Unique-ID Smart detection
Cross-Match Multi-dataset analysis
Role-Based Governed access
⇧
Enrollment_Oct.xlsx12,521 records analyzed
✓
Student ID detected99.9% unique · ready to match
Institutional Intelligence
Fall Enrollment · Current
Records12,521+150 new
Matched12,08496.5%
Changed3002.4%
Quality92%Healthy
Student Population by CollegeFiltered: Union
CurrentPrior Version
Cross-MatchStudent ID
Matched records8,446
Only in Tutoring24
Missing IDs7
Match quality99.6%
A Complete Data Intelligence Environment

From uploaded file to institutional insight—without rebuilding the application.

The platform is designed around dynamic datasets and metadata. New files can be introduced over time, analyzed automatically, governed by department and role, and used in reporting without requiring developers to manually create a new application screen or permanent table for every spreadsheet.

01

Smart File Ingestion

Upload CSV, XLS, or XLSX files. The platform reads headers, detects field types, creates dataset metadata, validates the upload, and prepares the file for controlled import.

02

Unique-ID Intelligence

Automatically evaluate Student ID, Faculty ID, Employee ID, Person ID, email, and other highly unique fields. See blanks, duplicates, uniqueness percentage, and confidence before confirming the key.

03

Dynamic Dataset Management

Manage datasets without manually coding a SQL table per file. Configure names, departments, visible fields, reportable fields, filterable fields, sensitive fields, and relationships.

04

Cross-Matching

Match two datasets even when their field names differ—such as Student_ID and Banner_ID. Identify matched records, records unique to either dataset, duplicate identifiers, and missing identifiers.

05

Version & Change Detection

Compare repeated uploads and immediately see new, removed, changed, and unchanged records. Drill into field-level changes for the same person or record across versions.

06

Interactive Reporting

Build filtered reports using selected columns, groups, sorting, counts, sums, averages, minimums, maximums, and practical medians—then visualize results and export them.

Cross-Match Engine

Connect datasets that were never designed to work together.

Create governed relationships between enrollment, tutoring, advising, academic performance, assessment, faculty, staff, survey, or operational datasets. The system does not require identical column names—administrators can define equivalent identifiers and preserve those mappings for future uploads.

  • Match using institution-defined identifiers
  • Compare one-to-one or operational usage data against master records
  • Identify records found only in Dataset A or only in Dataset B
  • Surface duplicate and missing identifiers before analysis
  • Build reports from the matched population

Tutoring Usage

Appointment-level dataset
Appointment IDIdentifier
Student_IDMatch key
ServiceCategory
Appointment DateDate
Student ID

Student Enrollment

Master student dataset
Banner_IDMatch key
CollegeCategory
MajorCategory
GPADecimal
8,446Matched
24Only in A
118Only in B
7Missing IDs
Version Intelligence

Know exactly what changed between uploads.

Repeated files become version history rather than isolated spreadsheets. Match versions by the confirmed unique identifier and show the institution the operational change—not just a new file name.

  • New records appearing in the latest version
  • Existing records with one or more changed fields
  • Records that no longer appear in the latest file
  • Unchanged records for baseline comparison
  • Field-level before/after values for review
Aug 1
Fall Enrollment · Version 112,250 records · baseline upload
Aug 15
Version 2 analyzedStudent ID matched across versions
187 new325 changed43 removed
Aug 29
Version 3 current12,521 records · reporting dashboards refreshed
Major changedGPA changedAdvisor changed
Data Quality · Fall EnrollmentLive Analysis
92%
Unique identifier completeness99.8%
Valid email format98.6%
Valid date values97.9%
Unexpected types12 flagged
Data Quality

Find problems before they become reporting problems.

The Data Quality workspace surfaces missing values, duplicate unique IDs, invalid dates, invalid email addresses, unexpected data types, empty columns, and identifier issues so administrators can review them before building institutional reports.

  • Duplicate review without automatic destructive deletion
  • Compare duplicates and choose which record should remain
  • Merge or flag records for follow-up where permitted
  • Audit administrator record corrections
  • Data quality scoring for rapid triage
Report Builder & Dashboards

Move from raw rows to decision-ready views.

Every appropriate field can become a filter, group, measure, or visualization input. Build reports for operational questions, student-success analysis, assessment, accreditation evidence, utilization, and institutional oversight.

  • Category, numeric, and date-aware filtering
  • Multi-select filters and server-side pagination
  • Count, sum, average, min, max, and median where practical
  • Bar, line, pie, doughnut, trend, KPI, and table views
  • Saved private, department, and institution-wide reports
  • CSV, Excel, and PDF export respecting active filters
Report Builder● Interactive
Tutoring + Student Enrollment
College
Students Using Tutoring
Campus: UnionFreshmanFall 2026
Business
Education
Health
Liberal Arts
Science
A Guided Workflow

Powerful enough for analysts. Clear enough for department users.

A guided workflow helps authorized users move safely from file upload to validated analysis while preserving administrator control over identifiers, mappings, sharing, and sensitive fields.

01
UploadCSV, XLS, or XLSX with department, description, and source information.
02
AnalyzeDetect columns, types, likely identifiers, duplicate values, and missing values.
03
ConfirmApprove the unique ID, field types, mappings, sharing rules, and sensitive columns.
04
ConnectMatch datasets, compare versions, and create reusable institutional relationships.
05
ReportFilter, visualize, save, share, and export decision-ready analysis.
Security & Governance by Design

Institutional intelligence requires institutional-grade controls.

The platform is designed for environments that may contain education records, employee information, identifiers, assessment information, and other sensitive institutional data. Security is enforced on the server side—not simply by hiding buttons in the interface.

Role-Based Access ControlSuper Administrators, Department Administrators, Standard Users, and Viewers receive explicit permissions, with server-side enforcement for protected actions.
Department GovernanceDatasets can belong to departments or be institution-wide. Administrators can independently control whether other departments may view, match, report from, or export a dataset.
Sensitive Field ControlsColumns such as Student ID, employee identifiers, email, date of birth, or personal contact information can be marked sensitive and restricted to authorized roles.
Secure Application ControlsPrepared database statements, CSRF protection, password hashing, input validation, session controls, file validation, login throttling, and protected error handling support a defense-in-depth approach.
Comprehensive Audit HistoryTrack logins, uploads, dataset changes, identifier changes, permissions, exports, reports, department assignments, and record-level edits with old/new values where appropriate.
Future Identity & Integration ReadyThe architecture can be extended for Microsoft Entra ID, Google authentication, SSO, Banner, CRM/SIS feeds, APIs, SFTP imports, scheduled reports, and data-warehouse connections.

Security, FERPA-related controls, retention, hosting, encryption, backups, integrations, and access policies should be configured and validated for each institution's environment and requirements.

Institutional Pricing

Configured around your data environment and reporting goals.

Institutions vary widely in dataset volume, number of departments, hosting requirements, integrations, reporting complexity, implementation support, and governance needs. We scope the platform around the environment rather than forcing every institution into the same package.

  • Implementation and data-governance planning
  • Department, role, and permission configuration
  • Dataset and reporting setup
  • Branding and terminology configuration
  • Training, launch support, and optional ongoing services
Talk With Us
Contact our sales team
We will review your institutional data sources, reporting goals, departments, cross-matching needs, security requirements, expected upload volume, and future integration priorities, then prepare a scoped proposal. Contact Sales

Email: contact@alahusolutions.com

Institutional Intelligence Platform

Stop managing disconnected files.
Start building institutional intelligence.

See how Alahu Solutions can configure a secure data, cross-matching, analytics, and reporting environment around your institution's workflows.

Request a Demo Back to Alahu Solutions