Enterprise Data Warehouse Services

The vendor is required to provide enterprise data warehouse (EDW) to institutional data management program and the design and implementation of a comprehensive EDW.
- Outcomes:
•    Create a “single source of truth” for the university’s data.
o    Implement an enterprise-wide EDW environment.
o    Develop a comprehensive modernization and EDW implementation roadmap.
•    Provide a secure, consistent, and reliable platform for data analysis, governance, and Institutional reporting 
o    Centralize institutional data from disparate systems into a unified data architecture.
o    Develop and assign standardized data definitions and metadata management against all data elements in all data models.
o    Develop scalable analytics and reporting platform with self-service capabilities.
o    Establish and improve data quality, lineage, and governance practices.
o    Enable support for advanced analytics use cases, including AI and ML modeling.
o    Support compliance with federal and state regulations.
•    Enable data driven decisions across university campuses.
o    Training and change management
o    Post-implementation support
1.    Implement post-implementation options for data services, monitoring, performance optimization, predictive analytics, AI and ML integration, and advanced use cases.
•    Generative AI and large‑language‑model services
o    Provide an out-of-the-box, secure chat interface that enables university users to ask natural-language questions and receive answers grounded in the enterprise data warehouse.
o    Host and maintain all required AI models; university will not manage model infrastructure.
o    Solutions must protect institutional data, supply basic accuracy and latency reporting, prevent hallucination, and include user training materials.
o    A 60-day pilot covering two data domains, measured against mutually agreed-upon metrics, will precede any campus-wide rollout.
•    EDW design and development
o    Propose technical architecture 
o    Identify platform, tooling, and infrastructure components for scalable implementation.
o    Build data pipelines (ETL/ELT), integrate existing data sources, and design and populate dimensional models.
o    Develop data quality and validation routines to ensure integrity of migrated data.
o    Implement security controls and compliance features in platform architecture.
•    Data governance and stewardship
o    Improve our data governance framework and institutional data standards.
o    Assist in implementing a metadata tagging strategy for all datasets, including data lineage, sensitivity, classification levels in accordance with the university data classification policy, and other relevant information.
o    Assist with the development of an enterprise data dictionary based on institutional terminology. 
•    Reporting and business intelligence enablement
o    Identify and configure dashboards and visualization tools (e.g., power bi, tableau).
o    Implement role-based access controls and enable self-service data access and auditing. 
o    Define and publish reusable data services and certified data assets like APIs, data marts, or official datasets.
o    Analyze and define current reporting needs and provide scope for developing needed reports.
- Non-technical platform requirements
•    User experience:
o    Interface design
1.    Provide a clean, responsive, and customizable interface that adapts to various devices (desktop, tablet, mobile).
2.    Should be compatible with desktop and mobile versions of major browsers including edge, chrome, Firefox and safari.
3.    Mobile-friendly application flows: ability to offer mobile-friendly application creation that provides a convenient and smooth experience for user.
4.    Training, reporting, and administration should be accessible via mobile devices such as iOS and android devices. 
5.    The preference is for access through mobile browser without need for an app.
6.    The interface should dynamically change based on the user’s role, presenting relevant tools and options.
7.    Simplify navigation to other areas of the software, such as forums, resources, and support services. 
8.    A well-maintained knowledge base with self-service materials for end-users. 
9.    All software components must adhere to the section 508 accessibility requirements and should level aa requirements.
•    Performance
o    Provide KPIs used by the supplier to measure performance of system components and any service level agreements for performance. 
•    Availability
o    Provide performance statistics that define and guarantee a specific amount of content throughput. 
o    Suppliers providing hosted solutions must be able to demonstrate robust security, encryption, and backup mechanisms to protect sensitive data. 
o    Define the system’s uptime and the frequency and impact of scheduled maintenance including updates. 
o    Define the proposed system’s set of environments such as dev, QA, prod, etc. 
•    Disaster recovery and business continuity
o    Security certifications: supplier commitment to data security best practices by utilizing industry-recognized security certifications.
o    Supplier security policies and procedures: detailed guidelines regarding incident response, vulnerability management, and ongoing commitment to staff training.
o    Regular communication about security updates: supplier transparency and prompt response commitment regarding the resolution of system issues, including security Updates and patches.
o    disaster recovery and business continuity: detailed disaster recovery and business continuity plans.
•    Support
o    Provide a detailed plan for continuity of service through escrow including regular updates to ensure continued access and usage of the software in the event the supplier ceases operations.
o    Define the process for submitting feature enhancement requests. 
o    Data migration services (or other value-add service).
o    Provide training for technical administrative staff to enable them to provide ongoing support and maintenance of any new technology platform that is implemented.
o    Define availability and mode of tech support.
o    Describe online user communities that exist for the proposed system. 
o    Data ownership, access and data migration in the university wishes to exit the partnership.