Smooth Sailing: How to Tackle CRM Integration Challenges (2026)

Customer Relationship Management systems have become essential infrastructure for higher education institutions seeking to improve student recruitment, retention, and overall operational efficiency. However, the path to successful CRM integration is rarely smooth. Institutions implementing CRM systems frequently encounter significant technical, organizational, and data-related obstacles that can derail projects, waste resources, and ultimately undermine the potential benefits these systems promise.

This comprehensive guide explores the major CRM integration challenges facing higher education institutions today, provides actionable solutions for each obstacle, and offers practical strategies for ensuring successful implementation. Whether you are an administrator planning a new CRM deployment, an IT professional managing integration efforts, or a faculty member affected by system changes, this article provides the insights you need to navigate the complexities of CRM integration successfully.

Understanding CRM Integration in Higher Education

Before exploring specific challenges, it is important to understand what CRM integration means in the higher education context. A Customer Relationship Management system in higher education serves as a centralized platform for managing interactions with prospective students, current students, alumni, donors, and other constituents. These systems typically integrate with admissions platforms, student information systems, financial aid systems, learning management systems, and various administrative databases.

Successful CRM integration means that data flows seamlessly between these various systems, that staff members across departments can access relevant information without manual data entry, and that the institution can leverage customer data to improve decision-making and constituent engagement. Poor integration, by contrast, leaves data trapped in separate systems, requires duplicate data entry efforts, creates opportunities for errors and inconsistencies, and prevents the institution from gaining a complete view of each constituent’s relationship with the institution.

The stakes of successful CRM integration are high. Higher education institutions invest significant financial resources in CRM platforms, often spending hundreds of thousands of dollars on software licenses, implementation services, and ongoing support. When integration fails or proceeds inefficiently, these investments yield diminished returns. More importantly, failed CRM implementations can damage institutional relationships with students, prospects, and donors when communication breaks down or constituent information is mishandled.

The Seven Major CRM Integration Challenges

Data Silos and Information Fragmentation

Data silos represent the most pervasive challenge facing higher education institutions attempting CRM integration. A data silo occurs when information remains trapped in isolated systems, inaccessible to other departments or disconnected from the central CRM platform. In higher education, this problem is particularly acute because institutions typically operate numerous legacy systems that evolved independently over many years.

For example, the admissions office may maintain a separate applicant tracking system, the student services office operates its own platform for tracking student interactions, the advancement office uses a separate donor management system, and the registrar maintains the official student information system. When these systems do not communicate with each other, advisors cannot see the complete history of a student’s interactions with the institution, development officers may contact students about giving opportunities without knowing they are struggling financially, and the institution cannot track which marketing initiatives actually lead to enrollment.

Data silos create several negative consequences. First, they result in an incomplete view of each constituent. Staff members make decisions based on partial information, leading to missed opportunities and inappropriate outreach. Second, silos necessitate duplicate data entry, as information entered in one system must be manually re-entered in others. This duplication consumes staff time and creates opportunities for errors and inconsistencies. Third, silos prevent the institution from leveraging data analytics effectively. Advanced analytics require consolidated data; when information remains scattered across multiple systems, institutions cannot identify trends, measure campaign effectiveness, or predict student success factors.

Addressing data silos requires a multi-faceted approach. First, institutions must conduct a comprehensive audit of existing systems and data sources. This audit should identify which data currently exists in which systems, how often data is updated, who owns responsibility for each data source, and which systems could potentially be consolidated or retired. Second, institutions should implement data integration tools and APIs that allow systems to communicate with each other. Rather than completely abandoning legacy systems immediately, many institutions use middleware solutions that translate data between systems automatically. Third, institutions should establish data governance policies that clearly define which system serves as the authoritative source for each type of information, preventing conflicts and inconsistencies.

Insufficient User Adoption and Change Resistance

A CRM system, regardless of how sophisticated its technology, is only as effective as its users. Insufficient user adoption represents a critical challenge that undermines CRM implementations across higher education institutions. Research indicates that user adoption rates significantly predict CRM project success; institutions with adoption rates above 80 percent typically realize the benefits promised by their CRM investment, while those with adoption rates below 60 percent struggle to justify their expenditure.

Resistance to CRM adoption in higher education stems from multiple sources. Many staff members have worked within existing processes for years or decades and perceive the new system as disrupting comfortable workflows. Faculty and staff may worry that CRM systems represent institutional surveillance or excessive focus on quantifiable metrics at the expense of holistic student development. Some users may simply lack confidence in their ability to master new technology. Others may resist because they fear the system will enable administrators to reduce staffing or consolidate departments. In some cases, users have had negative experiences with previous technology implementations and approach new systems with justified skepticism.

The consequences of poor adoption are substantial. When only a portion of staff actively use the CRM system, data entry becomes inconsistent, the system contains incomplete information, and colleagues who rely on that information make poor decisions based on partial data. Some staff members may continue using legacy systems in parallel with the CRM, creating additional work and introducing new opportunities for errors. The institution fails to achieve economies of scale or efficiency improvements that justified the initial investment. Departmental divisions may emerge between early adopters and resisters, creating tension and reducing collaboration.

Addressing user adoption challenges requires a comprehensive change management strategy, not merely technology training. First, institutions should clearly communicate why the CRM change is necessary and how it will benefit end users specifically. Rather than emphasizing institutional efficiency gains (which staff may perceive as threatening), messaging should focus on how the CRM enables staff to do their jobs better, access information more quickly, and provide better service to constituents. Second, institutions should involve end users early and extensively in the implementation process. When staff participate in selecting vendors, configuring workflows, and designing reports, they develop investment in the system’s success and gain confidence in their ability to use it.

Third, institutions must provide comprehensive, ongoing training that goes far beyond a single session or online module. Different user groups require different training approaches. Admissions staff need to understand how the CRM supports their recruitment workflows, while student services staff need training on tracking and documenting student interactions. Training should be role-specific, hands-on, and occur using the actual institutional data and workflows rather than generic examples. Fourth, institutions should establish peer mentors or super-users within departments who can provide immediate support and troubleshooting. Finally, institutions should celebrate early wins and success stories, sharing examples of how the CRM has enabled staff to serve students better or make decisions more effectively.

System Compatibility and Legacy System Integration

Most higher education institutions operate a complex ecosystem of systems and applications that evolved over many years. A typical institution might rely on 15 to 25 different software applications including the CRM, student information system, admissions system, learning management system, financial aid platform, accounting system, human resources system, facility management system, and various departmental databases. Integrating a new CRM with this complex landscape presents significant technical challenges.

Compatibility issues arise from several sources. Legacy systems may use outdated technology platforms and no longer receive vendor support. Some systems lack modern APIs (Application Programming Interfaces) that would enable them to share data with other applications. Different systems may use different database structures, making it difficult to map corresponding fields. Some systems may operate on different technology stacks, requiring complex translation layers. Additionally, some legacy systems have become deeply customized over the years, with undocumented modifications that make integration particularly challenging.

When CRM integration fails due to compatibility issues, the consequences are significant. Staff members may need to enter the same information into multiple systems, consuming time and introducing errors. Real-time data synchronization may not be possible, leaving different systems with outdated or conflicting information. Some manual processes that institutions hoped to automate remain necessary because automated integration proved impossible. The institution may need to maintain legacy systems longer than planned because the CRM cannot fully replace their functionality.

Addressing system compatibility challenges requires careful planning and realistic expectations. First, institutions should conduct a thorough technical assessment before selecting a CRM vendor. This assessment should document each existing system’s technical capabilities, the quality of available APIs, and the current vendor support status. Second, institutions should involve IT staff early in vendor selection, ensuring that the chosen CRM system can technically integrate with the existing environment. Third, institutions should consider a phased approach to integration, potentially moving quickly to consolidate systems that integrate easily while taking additional time to address complex integrations. Fourth, institutions may need to implement middleware solutions, data integration platforms, or custom integration code to bridge gaps between incompatible systems.

Some institutions face difficult decisions about legacy system modernization. If a critical legacy system cannot integrate with the new CRM due to age or technical limitations, the institution may need to retire the legacy system sooner than planned and migrate to a replacement that offers better integration capabilities. While this increases short-term costs and disruption, it can eliminate long-term technical problems and reduce ongoing maintenance burdens.

Data Quality Issues and Cleansing Challenges

Data quality represents an often-underestimated challenge in CRM integration. Higher education institutions typically accumulate vast quantities of constituent data over many years. However, this data is frequently incomplete, outdated, inaccurate, or inconsistent. Prospect names may be spelled multiple ways, email addresses may be outdated, phone numbers may be missing, addresses may be incomplete, and duplicate records may exist for the same person. When this poor-quality data is migrated into the new CRM system, it undermines the system’s effectiveness from day one.

Data quality problems in higher education have specific characteristics. Student names may be recorded inconsistently due to cultural naming conventions, preferred names versus legal names, and name changes. Email addresses and phone numbers become outdated quickly as students graduate and move. Institutional relationships are complex, with individuals potentially serving as prospect, student, parent, employee, and donor simultaneously, yet these relationships may not be captured consistently. Biographical information collected years ago may contain errors that were never corrected. Address information is particularly problematic, with many records containing incomplete addresses or addresses from years past.

The consequences of poor data quality are substantial. Analytics and reporting become unreliable when built on flawed data. Business intelligence initiatives that should inform strategic decisions instead provide misleading information. Personalized communication campaigns fail when email addresses are incorrect or names are misspelled. Constituent records become difficult to match across systems, leading to further duplication. Institutional compliance efforts, such as those related to federal student loan servicer requirements, may be compromised. Perhaps most importantly, poor data quality undermines trust in the system; when staff members encounter incorrect information, they lose confidence in the system’s reliability.

Addressing data quality requires both preventive and remedial approaches. Prior to CRM migration, institutions should conduct comprehensive data cleansing efforts. This process involves multiple steps: first, identifying and removing duplicate records; second, standardizing data formats (for example, ensuring all phone numbers follow the same format); third, validating data completeness and identifying missing information; fourth, correcting obvious errors (such as impossibly early birth dates); and fifth, flagging suspect or questionable data for manual review. Automated data quality tools can assist with this process, but human review remains necessary for complex decisions.

Institutions should also establish clear data governance policies that define data entry standards, assign ownership responsibility for data quality, and establish periodic audits to catch errors early. Some institutions designate data stewards for each major business area who take responsibility for data quality within their domain. Ongoing training for staff members who enter data ensures that new records maintain quality standards. Finally, institutions should implement validation rules within the CRM system that prevent obviously incorrect entries, such as birth dates in the future or phone numbers with invalid formats.

Inadequate Planning and Unclear Objectives

Many failed CRM implementations can be traced to inadequate planning in early project phases. While this challenge is more organizational than technical, it creates cascading problems throughout the integration process. Institutions that rush into CRM selection and implementation without clearly defining their needs, goals, and success metrics frequently discover that the chosen system does not align well with institutional priorities.

Planning failures manifest in several ways. Some institutions purchase CRM systems to solve problems they have not clearly defined. For example, an institution might implement a CRM hoping to improve student retention without first analyzing what factors actually predict retention at that specific institution. Others implement CRM systems without securing adequate executive sponsorship or funding, leading to project delays and incomplete implementations. Still others fail to conduct adequate stakeholder engagement, resulting in a system that does not reflect the needs of key user groups. Some institutions underestimate the complexity of implementation, creating unrealistic timelines that pressurize teams and lead to corner-cutting.

The consequences of inadequate planning extend throughout the implementation. The institution may select a CRM system that does not address its core needs, requiring costly changes or replacements later. Implementation budgets may be inadequate, leading to deferred features, delayed integration work, or insufficient training. Conflicting expectations among different stakeholder groups may emerge during implementation, creating political tensions. Timelines may slip repeatedly, delaying the institution’s ability to realize benefits and consuming staff time on implementation work rather than their regular duties.

Addressing planning challenges requires disciplined project governance. First, institutions should conduct a comprehensive needs assessment that identifies current pain points, desired future capabilities, and specific metrics for measuring success. This assessment should include input from major stakeholder groups across the institution. Second, institutions should establish clear project goals and success criteria before evaluating vendors. Third, institutions should secure executive sponsorship and adequate funding before proceeding with implementation. Fourth, institutions should allocate realistic timelines that account for the complexity of integration work, data migration, user training, and change management. A typical CRM implementation in higher education requires 12 to 18 months from vendor selection to full operational deployment; institutions that expect to achieve results in six months are setting themselves up for failure.

Scalability and Customization Limitations

Higher education institutions are dynamic organizations. As institutions grow, expand into new markets, add new degree programs, or shift strategic priorities, their CRM needs evolve. Selecting a CRM system that cannot scale with the institution or customized to accommodate unique institutional needs creates long-term problems. Institutions that outgrow their CRM systems face expensive replacements or perpetual workarounds that undermine system effectiveness.

Scalability challenges in CRM systems emerge in multiple dimensions. As the number of users increases, some CRM systems experience performance degradation. As the volume of data grows, systems designed for smaller organizations may become slow or unwieldy. As the number of integrated systems increases, some CRM platforms struggle to maintain synchronization. Additionally, as institutions’ needs evolve, they may discover that their chosen CRM system lacks features or capabilities that have become important.

Customization challenges frequently arise from vendors’ desire to maintain standardization across their customer base. Some CRM vendors provide limited customization options, requiring institutions to modify their business processes to fit the system rather than customizing the system to fit institutional processes. This approach works well for some institutions but creates significant challenges for others, particularly large research universities with complex constituent management needs or specialized institutional structures.

Institutions should evaluate scalability and customization capabilities carefully during vendor selection. Questions to explore include: How does the system perform as user counts and data volumes increase? What customization options are available? Does the vendor permit custom development or integration code? What is the vendor’s roadmap for new features? How frequently are updates released? Are customizations preserved when the system is updated? Institutions should also consider their growth plans over the next five to ten years and select systems that can accommodate anticipated expansion without major redesign.

Staff Resource Constraints and Implementation Complexity

Successful CRM implementation requires significant staff resources, yet higher education institutions frequently underestimate these requirements. CRM projects require expertise in multiple domains: technology project management, systems administration, database design, business process analysis, change management, and user training. Many institutions lack adequate in-house expertise and must rely on vendor professional services or external consultants, significantly increasing implementation costs.

Resource challenges manifest in several ways. IT departments already stretched thin with regular maintenance and support duties struggle to allocate staff to CRM implementation work. Business analysts capable of understanding institutional processes and translating them into system requirements may not be available in-house. User training cannot be conducted adequately because insufficient staff are available to deliver training across the institution. Key institutional staff who could serve as super-users or change advocates are unavailable because they are required for their regular duties. The project extends far longer than initially expected because insufficient resources are allocated to complete work on schedule.

When institutions lack adequate resources, implementation quality suffers. Configuration work may be incomplete or rushed. Data migration may be inadequate, resulting in poor data quality in the new system. Training may be minimal, leading to poor user adoption. Integration work may be deferred indefinitely, leaving the system operating in isolation from critical institutional systems. The institution eventually realizes that the CRM system it implemented does not actually meet its needs and requires expensive customization or replacement.

Addressing resource constraints requires honest assessment of in-house capabilities and realistic budgeting for external support. Institutions should not assume that IT staff can implement a major CRM system while continuing to perform all regular duties. Instead, institutions should either hire additional staff, budget for vendor professional services, or reduce regular duties during the implementation period. Vendor selection should consider not just software cost but also the vendor’s service delivery model and professional services costs. Some vendors provide more comprehensive implementation support than others. Institutions should also build into their budgets ongoing training and support resources that continue after the initial implementation.

Vendor and Technology Selection Errors

The CRM vendor and technology platform selected has profound implications for integration success. Institutions that select inappropriate vendors or platforms discover later that their choice creates integration challenges that prove difficult and expensive to overcome. Common selection errors include choosing systems based primarily on price without adequate evaluation of functionality or integration capabilities, selecting systems that do not align with the institution’s technical infrastructure, or choosing vendors with weak support and professional services capabilities.

Vendor selection should be a rigorous process involving technical evaluation, cost analysis, and reference checks. Institutions should evaluate not only the software itself but also the vendor’s stability, support capabilities, and service delivery model. Questions to explore include: How long has the vendor been in business and how financially stable are they? What is the quality of their technical support and how quickly do they respond to issues? Do they maintain a partner ecosystem of integration specialists? What is their professional services delivery model and pricing? How frequently do they release software updates? What is their roadmap for future enhancements?

Essential Integration Strategies and Best Practices

Comprehensive Pre-Implementation Assessment

The foundation for successful CRM integration is established during the pre-implementation phase through comprehensive assessment work. This phase typically extends four to eight weeks and involves deep analysis of current state processes, systems, and data. A thorough assessment identifies integration requirements, data migration challenges, and organizational change needs before implementation begins, when addressing these issues is far less expensive than managing them during or after implementation.

A comprehensive assessment should include the following elements:

• Current state documentation: Detailed mapping of existing systems, data sources, key business processes, and current workflow. This documentation becomes the reference point for understanding what needs to change.
• System inventory: Complete inventory of all applications and databases the CRM must integrate with, including technical specifications, API capabilities, and current vendor support status.
• Data audit: Assessment of data quality, completeness, and consistency across existing systems. This audit identifies data cleansing work that must occur prior to migration.
• User needs analysis: Interviews with key stakeholder groups to understand their current challenges, desired capabilities, and concerns about the new system.
• Technical infrastructure assessment: Evaluation of current IT infrastructure, network capacity, security capabilities, and readiness to support new systems.
• Risk assessment: Identification of key risks to implementation success and development of mitigation strategies.
• Resource requirements: Realistic assessment of staff resources required for successful implementation, including both internal staff and external consulting services.
• Success metrics definition: Clear definition of how success will be measured, including specific metrics related to user adoption, data quality, system performance, and business outcomes.

Phased Implementation Approach

Rather than attempting to implement a CRM system across an entire institution simultaneously, most institutions benefit from a phased approach that implements functionality and integrations in waves. A phased approach allows institutions to build momentum, learn from early phases, and address challenges before they cascade into larger problems.

A typical phased approach might look as follows:

Phase 1 (Months 1-4): Core system deployment focusing on the CRM platform itself, basic configuration, initial user groups (perhaps admissions and enrollment staff), and foundational data migration. This phase establishes operational familiarity with the system and core processes without the complexity of full institutional integration.

Phase 2 (Months 4-8): Integration of the most critical legacy systems, typically the student information system and enrollment management system. This phase enables the CRM to become a primary data source and point of access for key institutional data.

Phase 3 (Months 8-12): Expansion to additional user groups such as student services, academic advising, and retention staff. This phase broadens CRM adoption and addresses student lifecycle management beyond admissions.

Phase 4 (Months 12-18): Integration of advancement and development systems, enabling comprehensive constituent relationship management across prospective students, current students, alumni, and donors. This phase creates the unified constituent view that justifies much of the CRM investment.

This phased approach distributes implementation complexity, allows time for change management work between phases, and enables the institution to realize early benefits that build confidence in the system and support for continued implementation. Institutions that attempt to implement everything simultaneously often encounter overwhelming complexity that leads to extended timelines and poor outcomes.

Data Migration and Preparation Strategy

Data migration represents one of the most critical and complex aspects of CRM implementation. The quality of data migrated into the new system determines the system’s initial value and user confidence. A poor data migration that results in incomplete, inaccurate, or inconsistent data undermines the CRM from day one and requires years to repair.

A sound data migration strategy includes several key elements. First, institutions should conduct comprehensive data cleansing prior to migration. This process involves identifying and removing duplicate records, standardizing data formats, validating completeness, correcting obvious errors, and flagging suspect data for manual review. Institutions should allocate 4 to 8 weeks for data cleansing work and budget for both technological solutions and manual review work. Some institutions find that hiring temporary staff to conduct manual data review is cost-effective.

Second, institutions should carefully plan data mapping, ensuring that fields from legacy systems are accurately translated to corresponding CRM fields. This mapping should document not only which fields map to which but also any transformations necessary (for example, converting data formats or calculating derived fields).

Third, institutions should conduct test migrations before the production migration. Test migrations identify problems in advance, allowing time to address them before the actual migration that will disrupt operations. Fourth, institutions should develop rollback plans in case migration issues require reverting to the legacy system temporarily while problems are corrected.

Fifth, institutions should plan for post-migration data validation. Immediately after migration, staff should verify that data has been accurately transferred by comparing record counts, spot-checking individual records, and validating that critical information has migrated correctly. Any discrepancies should be identified and corrected quickly while the migration work is still fresh in staff members’ minds.

Change Management and User Adoption Strategy

Technology implementations ultimately succeed or fail based on user adoption and behavioral change. A comprehensive change management strategy is therefore as important as the technical implementation work. Effective change management includes multiple components: clear communication, user involvement, comprehensive training, early quick wins, and ongoing support.

Communication strategy: Develop a communication plan that explains why the CRM change is necessary, what benefits it will provide, and how it will be implemented. Messaging should emphasize benefits to end users specifically (such as faster access to information or reduced manual work) rather than only institutional benefits (such as efficiency or cost reduction). Communication should be frequent and ongoing throughout the implementation, sharing progress updates, addressing concerns, and celebrating milestones.

User involvement: Involve end users extensively in the implementation process rather than surprising them with a finished system. User involvement can include participation in vendor selection, configuration of workflows and processes, design of reports and interfaces, and testing of the system before go-live. When users participate in implementation decisions, they develop investment in the system’s success.

Training strategy: Develop comprehensive, role-specific training that prepares each user group for the work they will do in the new system. Training should occur close to go-live timing so that knowledge remains fresh. Training should be hands-on and use actual institutional data and workflows rather than generic examples. Training should include both formal sessions and ongoing support mechanisms such as help desks and online resources.

Super-user program: Identify and train super-users within each department who can provide first-line support and serve as change advocates. Super-users become trusted resources for colleagues and can reinforce training messages using language and context familiar to their colleagues.

Quick wins: Identify opportunities to demonstrate early value from the CRM system. Perhaps the CRM enables the admissions office to respond to student inquiries faster, or enables advisors to identify students at risk of dropping out. Publicizing these early successes builds confidence in the system and supports broader adoption.

Comparison of CRM Implementation Approaches

Approach	Timeline	Risk Level	Cost Impact	Best For
Big Bang (Simultaneous)	6 to 12 months	Very High	Lower upfront, high remediation	Small institutions with simple systems
Phased Implementation	12 to 18 months	Moderate	Moderate, distributed over time	Most higher education institutions
Parallel Running	18 to 24 months	Low	Highest (dual system costs)	Mission-critical operations requiring high confidence
Pilot Program	Variable, 6 months+ for initial pilot	Low for pilot, moderate for expansion	Moderate, testing before large commitment	Risk-averse institutions or uncertain technical requirements

Critical Success Factors for CRM Integration

Research on higher education technology implementations identifies several critical factors that distinguish successful projects from failed ones. Institutions should ensure these success factors are present in their CRM implementation approach.

Executive Sponsorship and Commitment

Successful CRM implementations require strong executive sponsorship from high-level leaders. An executive sponsor serves multiple functions: securing necessary funding and resources, providing air cover for staff members undertaking change work, resolving cross-departmental conflicts that arise during implementation, and publicly demonstrating institutional commitment to the initiative. Without executive sponsorship, implementation projects frequently stall when challenges arise.

Effective executive sponsors are typically senior leaders with authority across multiple departments, such as the provost, vice president for enrollment management, or vice president for student affairs. The sponsor should have direct authority over most of the departments affected by the CRM implementation, or at minimum should have strong relationships and credibility with those departments.

Clear Project Governance and Oversight

Effective project governance structures provide oversight, decision-making authority, and escalation paths for implementation issues. A typical governance structure includes a steering committee of senior leaders who provide strategic direction and resolve escalated issues, a project management office that manages day-to-day implementation activities, and working teams focused on specific implementation areas such as technical integration or training.

Clear governance structures prevent implementation projects from becoming political battlegrounds where different departments fight over resources and configuration decisions. Regular steering committee meetings (typically monthly) ensure that senior leaders remain informed about progress and challenges and can intervene quickly when issues arise.

Adequate Staffing and Expertise

As discussed earlier, CRM implementations require significant staff resources. Successful institutions allocate adequate staff to implementation work, understanding that this work cannot be handled in addition to regular duties. Some institutions hire dedicated project managers and business analysts specifically for the CRM implementation. Others work with vendor professional services teams to supplement in-house capacity. Most successful implementations involve some combination of internal staff and external expertise.

Realistic Timelines and Expectations

Institutions that expect to implement a comprehensive CRM system across their entire organization in six months are setting themselves up for failure. A realistic timeline acknowledges the complexity of integration work, allows adequate time for testing and change management, and builds in contingency for inevitable challenges. Most higher education CRM implementations require 12 to 18 months from vendor selection to full operational deployment across the institution. Institutions should resist pressure to accelerate timelines beyond what is realistic; compressed timelines typically result in cut corners that create problems for years afterward.

Addressing Integration Challenges by System Type

Student Information System Integration

Key considerations for SIS integration include determining which data will be synchronized in