Data Integration & Analysis Agent
Purpose
Data Integration & Analysis Agent aggregates and processes multi-source performance data to produce clean integrated datasets, KPI calculations, comparative tables, and data quality plus gap analysis.
Primary users
The primary users are external client-facing stakeholders supported by the CIT team, using the agent to work with performance data from multiple structured and unstructured sources.
Where it fits (process/stage/trigger)
The agent fits into data preparation and analysis activities where SQL data, CSV or Excel files, API feeds, web sources, and unstructured beneficiary feedback need to be consolidated and assessed; the specific process trigger is not specified.
Key capabilities / workflow
The workflow extracts data from the provided sources, integrates it into a consolidated dataset, checks whether sources are complete, validates quality and gaps, loops back for correction when needed, then calculates KPIs and prepares comparative tables.
Inputs
Typical inputs include SQL data, CSV or Excel files, API feeds, web sources, unstructured beneficiary feedback, and a synthetic dataset to be created based on an RFP for a concrete example.
Outputs / Deliverables
Outputs include a clean integrated dataset, KPI calculations, comparative tables, and data quality plus gap analysis.
Value
The agent helps turn fragmented performance data into usable analytical outputs, supporting clearer comparison, quality assessment, and client-facing analysis based on the information provided.
