Inspiring Excellence: Education BI Analytics
Data-driven student outcomes and district-wide performance analytics
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Data-driven student outcomes and district-wide performance analytics
By Errin O'Connor, Founder & Chief AI Architect, EPC Group
EPC Group helped a public education organization serving 28,000+ students across 45 schools implement Microsoft Power BI for student performance analytics. The platform tracks at-risk students within the first 6 weeks of each semester — enabling early intervention before a student fails a grading period. The organization's mission: "inspiring excellence — every child, every day."
EPC Group assisted a public education organization in implementing Power BI. This tool helps track student performance across all schools. It also improves graduation rates through early intervention analytics.
Additionally, Power BI enables data-driven funding allocation. This ensures that every child receives the resources they need to succeed.
12%
Graduation Rate Increase
45
Schools Connected
28K+
Students Tracked
85%
At-Risk Early Identification
This public education organization serves over 28,000 students across 45 schools in multiple districts. It is committed to its mission of “inspiring excellence -- every child, every day.”
However, the organization faced challenges due to a lack of analytics infrastructure. Important data on student performance, attendance, behavior, and demographics was stored in different systems. This separation made it difficult to:
Fragmented student data: Academic records were stored in the Student Information System (SIS). Attendance data was kept in a separate platform. Behavioral incidents were tracked in another system. Special education (IEP) data was in a dedicated tool. This separation meant there was no single view of the whole student.
Late intervention for at-risk students: Struggling students are often identified too late. They usually get recognized only after failing a grading period or missing too many classes. This delay results in a major drop in the success rates of interventions.
Inequitable resource allocation: Funding for tutoring programs, after-school activities, and counseling services relied on anecdotal evidence and past budgets. This approach did not consider current student needs data, resulting in mismatched resources.
State reporting burden: Preparing state-mandated accountability reports required weeks of manual data reconciliation across systems. Errors in state submissions risked funding penalties and accreditation issues.
EPC Group developed a comprehensive Power BI analytics platform tailored for K-12 education. This platform merges student data from various systems into one analytics layer.
It offers:
All of this is achieved while maintaining strict FERPA compliance.
We developed a unified student profile dashboard. This dashboard combines academic performance, attendance patterns, behavioral data, and IEP/504 accommodations.
Teachers and counselors can access a complete picture of each student. They can also perform trend analysis and peer comparisons.
We developed a predictive analytics model to assess students' dropout risk. This model uses:
At-risk students are identified and provided with recommended interventions before they reach critical points.
We deployed dashboards across the district to compare school performance. These dashboards include data on standardized assessments, graduation rates, college readiness indicators, and equity metrics.
Superintendents and school board members can access real-time data to support their policy decisions.
We developed data models that link student needs to available resources. These resources include:
Now, decision-makers allocate resources based on current student data rather than historical precedent.
The early warning system identified 85% of at-risk students within the first 6 weeks of each semester. This enabled timely intervention. Over two academic years, the district-wide graduation rate increased from 78% to 90%.
The largest improvements were observed in:
Funding allocation dashboards revealed that three schools had very low counseling resources for their at-risk student populations. By rebalancing these resources, the schools saw a 20% increase in student retention rates within one year.
The predictive early warning model accurately identifies 85% of students at risk of failing or dropping out. This provides counselors and teachers with 4-6 weeks of advance notice.
This lead time allows for the implementation of targeted interventions, such as:
The preparation of state accountability reports has significantly improved. It now takes only 2 days instead of the previous 3 weeks of manual work.
Data validation rules are built into the Power BI data pipeline. These rules spot inconsistencies before submission. This process helps avoid the data quality issues that resulted in state audits in the past.
Power BI dashboards now track performance, attendance, and discipline data by demographics. This helps the district identify and address equity gaps.
The achievement gap between demographic subgroups narrowed by 8 percentage points in math proficiency.
More than 1,200 educators access student performance dashboards every day. Of these, 92% say the data helps them tailor instruction and find students who need extra support.
Additionally, principals utilize school-level dashboards for planning staff development.
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“Before EPC Group implemented Power BI, we were making resource allocation decisions based on gut feeling and historical precedent. Now every principal and counselor has a dashboard that shows exactly which students need support and what kind of intervention is most likely to help. Our graduation rate improvement speaks for itself -- but more importantly, we're catching kids before they fall through the cracks. That's what 'every child, every day' actually looks like in practice.”
Power BI enables school districts to build early warning systems that combine academic performance, attendance trends, behavioral incidents, and demographic data into predictive risk scores for every student. By identifying at-risk students within the first 6 weeks of each semester -- before they fail a grading period or accumulate excessive absences -- counselors and teachers can intervene early with tutoring, mentoring, and family outreach programs that have significantly higher success rates than late-stage interventions.
Yes, Power BI is FERPA compliant when properly configured with Microsoft 365 education licensing, Azure Active Directory, and appropriate row-level security (RLS). EPC Group implements role-based access controls so teachers see only their students, principals see their school, and district administrators see aggregated data. PII masking on reports shared outside the district, audit logging of all data access, and encryption at rest and in transit ensure full FERPA compliance.
Power BI connects to all major student information systems including PowerSchool, Infinite Campus, Skyward, Tyler SIS, Aeries, and others through direct database connections, APIs, or automated data exports. EPC Group builds ETL pipelines using Azure Data Factory or Power BI Dataflows that extract student data from these systems alongside attendance platforms, behavioral tracking tools (SWIS), IEP/504 management systems, and state assessment data feeds to create a unified analytics layer.
A typical K-12 Power BI implementation takes 14-22 weeks depending on the number of schools, data sources, and complexity of analytics requirements. EPC Group follows a phased approach: data assessment and information architecture (weeks 1-4), data platform build and ETL pipelines (weeks 5-10), dashboard development with educator feedback (weeks 11-16), and phased rollout with role-specific training for teachers, counselors, principals, and district leadership (weeks 17-22).
Absolutely. Power BI dashboards can disaggregate academic performance, attendance, discipline, and college readiness data by race, ethnicity, gender, socioeconomic status, English learner status, and special education designation. This enables districts to identify and quantify equity gaps with data rather than anecdotes, set measurable equity goals, track progress over time, and demonstrate accountability to school boards, communities, and state departments of education.
Power BI automates the data preparation process for state accountability reports by building data validation rules directly into the analytics pipeline. Data quality checks catch inconsistencies -- such as mismatched enrollment counts, missing demographic codes, or invalid assessment scores -- before submission rather than after a state audit flags them. Districts using EPC Group's Power BI implementations have reduced state report preparation time from 3+ weeks to 2-3 days.
EPC Group focuses on Power BI for education. We have strong expertise in:
Schedule a free consultation.
EPC Group assisted a public education organization that serves over 28,000 students across 45 schools. They implemented Microsoft Power BI for analyzing student performance.
The platform identifies at-risk students within the first 6 weeks of each semester. This allows for early intervention before a student fails a grading period.
The organization’s mission is: "inspiring excellence — every child, every day."
The organization was committed to its mission but lacked analytics infrastructure to translate that vision into measurable results. Key problems:
EPC Group built a Power BI analytics platform connecting the Student Information System (SIS), attendance data, assessment scores, and intervention records into a unified early-warning system.
The key innovation was identifying at-risk students early enough to intervene effectively.
Student data is protected under FERPA. EPC Group built the platform with FERPA compliance from the start.
The engagement followed a phased approach over 22 weeks.
EPC Group develops various tools to enhance student performance. These include:
All dashboards comply with FERPA regulations. They feature row-level security, ensuring that each user only accesses their authorized student population.
Power BI connects to the Student Information System, attendance records, and assessment data. A DAX model calculates risk scores based on:
Students who cross the threshold appear in the counselor's alert dashboard within 6 weeks of the semester start. This timing allows for early intervention before failure.
Yes, this is possible with the right setup. EPC Group uses row-level security to ensure that:
Executive dashboards display overall trends without revealing individual student personally identifiable information (PII). Additionally, data residency remains within your Microsoft 365 tenant.
EPC Group delivers FERPA-compliant Power BI analytics for K-12 school districts and education organizations. Call (888) 381-9725 or request a 30-minute discovery call.
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