Business Intelligence and Data Warehouse Generative BI Data Analytics Services

The Vendor is required to provide business intelligence and data warehouse (BI&DW) architecture/platform to be capable of generative bi (GenBI), which is the latest evolution of traditional bi by combining artificial intelligence, machine learning (AI/ml), and also generative artificial intelligence (GenAI) with traditional analytics tools to provide deeper insights, predictive analytics, and automated decision-making capabilities. 
- GenBI helps make analytics data more useful and accessible for business users, data analysts, and technical developers alike.
- Self-service Analytics for Democratized Data Access
•    Enable users to ask the GenBI tools, in plain language, to conduct advanced analytics and build reports without the need to learn special programming languages specific to a traditional data analytics tool.
•    Empower users at all levels within agency to access and interpret data, without the need to rely on technical developers to transform data and build charts from scratch.
- Automation for Improved Efficiency
•    Automate repetitive tasks to reduce the need for manual data analysis and interpretation, allowing business stakeholders to focus on essential/ strategic work, instead of cleansing/transforming data.
•    Auto-generate insights and recommendations, revealing meaningful patterns or insights leading to faster decision-making.
- Advanced Analytics for Predictive Capabilities
•    Leverage machine learning and artificial intelligence to generate predictive insights to anticipate future trends and opportunities.
•    Process larger volumes of complex data, enabling analysis of previously inaccessible insights.
- Data Decoupling for Increased Data Security
•    Decouple data from public-facing AI solutions like ChatGPT to protect privacy and mitigate data security concerns with sharing sensitive/confidential data with a public Large Language Model (LLM).
•    Avoid challenges associated with uploading large amounts of organizational data to a public LLM.
- Identifying Impactful GenBI Use Cases
•    Engagement manager will be responsible for managing vendor’s resources, creating working plan, providing weekly status reports, and ensuring high-quality deliverables.
•    Review and assess the existing inventory of BI use cases (47 use cases) to identify select use cases that can potentially be high impact and/or architecturally significant GenBI use cases.
•    In addition, review the existing inventory of agency AI ideas/business requests to cross reference and/or reconcile with BI use cases to reach a set of candidate GenBI use cases for prioritization.
•    Develop Return on Investment (ROI) calculations, incorporating cost-benefit analysis, as well as other additional and pertinent criteria for prioritizing GenBI use cases.
•    Conduct meetings, workshops and interviews with key business stakeholders and operational teams to finalize and document detailed requirements for 5 impactful GenBI use cases.
•    Create detailed requirement documents of each GenBI use case, including goals, required data inputs, expected outcomes, and the acceptance criteria.
•    Complete risk assessments by collaborating with Enterprise IT Governance, Information Security Office, Legal, and Compliance teams to identify data privacy, regulatory, and technical risks. 
•    Host prioritization workshops with cross-functional teams to rank use cases based on impact, feasibility, and risk factors.
- Architecture/Design to Expand Current BI&DW Platform with GenBI / Agentic AI capabilities
•    Engagement manager will be responsible for managing vendor’s resources, creating working plan, providing weekly status reports, and ensuring high-quality deliverables.
•    Propose a GenBI / agentic AI platform architecture/design that has GenBI / agentic AI capabilities
•    (To-Be), features and benefits as mentioned in the Introduction section.
•    Review and assess all aspects of the current BI&DW platform architecture (As-Is) including but not limited to tools, data sources/models/pipelines, integration points/interfaces, BI workflows and processes, etc.
•    Perform a gap analysis between the as-Is and To-Be, as well as providing an actionable roadmap on how to advance agency BI platform from as-Is to To-Be.
•    Demonstrate the viability of a proposed GenBI / agentic AI platform.
•    Implement the proposed GenBI / agentic AI architecture & platform.

- Contract Period/Term: 1 year
- Questions/Inquires Deadline: July 09, 2025