Core job | Give institutional data teams a higher education data foundation with modeling, governance, analytics, and AI tools. | Run the data foundation and turn it into answers, recurring reports, monitoring, predictive work, and AI workflows for campus teams. | Edify equips the data team. Doowii extends it. |
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Operating model | EAB offers self-service, partially managed, and fully managed versions of Edify, with professional services available around the platform. | Doowii's default model is managed end to end. Our team connects the systems, configures the model, runs the platform, and maintains it as needs change. | With Doowii, ongoing platform work is part of what you are buying. |
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How you start | EAB describes establishing a core platform, connecting core systems, and adding custom models and deliverables through iterative projects. | Doowii can begin with one enrollment, student success, institutional research, or other campus priority and only the systems needed to solve it. | A team, college, or department can get value without waiting for an institution-wide rollout. |
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Higher education model | EAB reports 150+ modeled entities or super tables and 200+ customizable data and metadata definitions, with default transformations and plain-language definitions. | Doowii starts with education concepts, then maps the institution's terminology, relationships, rules, permissions, and metric definitions into the model. | Doowii makes adapting and maintaining the model part of the managed service. |
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Integration and maintenance | EAB reports 15+ connectors plus transformation, validation, deduplication, processing logs, monitoring, and other data-quality tools. | Doowii handles source access, identity mapping, field mapping, quality checks, refresh schedules, monitoring, and ongoing changes to source systems. | Doowii owns the operational work between connecting a source and keeping it useful. |
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What campus teams get | Edify includes no-code and low-code analysis, reporting, predictive modeling, BI delivery, Query Assist, Data Search Assist, and SQL Explainer. | Teams can ask questions in plain language, use shared pinboards, receive recurring reports, monitor indicators, and run predictive and AI workflows on governed data. | Doowii is built to deliver usable work to campus teams, not only a governed data layer. |
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Role of AI | Edify uses AI to help people query data, find information, and understand SQL within its data-management environment. | AI is part of how people use Doowii and how the platform completes recurring analytical work, while showing the data, definitions, and methodology behind the result. | Doowii uses AI as part of the operating experience, not only as an assistant beside the warehouse. |
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Governance | Edify includes cataloging, business definitions, permissions, row-level security, quality monitoring, validation, lineage, data search, and snapshotting. | Institutional data leaders own definitions, permissions, and review. Doowii applies those decisions across the data model, reports, analysis, models, and AI workflows. | The institution keeps oversight without having to operate every layer of the platform. |
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Existing data stack | Edify can ingest from campus systems and deliver data to BI tools and other downstream destinations from its AWS-hosted environment. | Doowii can work with an existing warehouse or provide the foundation. Enterprise deployments can also expose normalized Iceberg tables to approved tools. | Doowii can serve as the AI data team without forcing a warehouse replacement. |
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Deployment options | EAB describes Edify as an AWS-hosted platform with several service levels. | The standard model is fully managed. When the architecture requires it, Doowii can also use institution-owned storage and dedicated query compute inside the institution's VPC and region. | Deployment flexibility is available, but the core value remains the managed platform and the team operating it. |
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