April 2026 monthly summary for prefeitura-rio/queries-rj-sms: Focused on delivering data-model and data-infrastructure enhancements to enable accurate targeting for PIC program, improved data quality, and scalable analytics. Implemented deduplication improvements and schema fixes, added APS patient data integration, expanded query capabilities, and established chatbot data surfaces to support automation and reporting. Demonstrated strong cross-team collaboration with APS and Iplan efforts, setting a foundation for better program insights and patient care coordination.

March 2026 — prefeitura-rio/queries-rj-sms. The month delivered end‑to‑end data pipeline and analytics enhancements focused on maternity messaging workflows, CNES data ingestion quality, and foundational SISARE/PGM groundwork. Key outcomes include improved data quality, governance, and readiness for downstream analytics, with direct business value in scheduling accuracy, operational reporting, and cross-system data lineage.

February 2026 monthly summary for prefeitura-rio/queries-rj-sms: Focused on data integrity and SIPNI alignment for home-visit data. Implemented feature to filter home visit records to ACS professionals by classification code and refactored SQL column names to align with the updated SIPNI base model. Resulting changes improve data accuracy, schema clarity, and downstream reporting.

January 2026: Completed a critical data-pipeline maintenance fix in the prefeitura-rio/pipelines_rj_sms project by aligning the Google Sheets integration with the renamed Equipe JR column. This ensured data consistency, reduced downstream reconciliation effort, and improved reliability of the pipeline's reporting data. The change was committed in c7badee863b8b08aac83a43a8fbee1c8ddb4612d with the message 'Changing the new name of the Equipe JR column'.

December 2025 monthly summary for prefeitura-rio/queries-rj-sms: Implemented data modeling and reporting enhancements to strengthen subway project analytics and PGM reporting. Delivered a new patient data table with cleaning/standardization, renamed schemas, and data exclusions to improve data quality and reliability. Expanded PGM reporting with templates/models and naming conventions; fixed a SQL syntax bug to ensure templates execute reliably. Business value: cleaner insights, more reliable dashboards, and faster, consistent reporting across programs.

Month 2025-11: Delivered a coordinated set of data-model and pipeline enhancements across prefeitura-rio/queries-rj-sms and prefeitura-rio/pipelines_rj_sms, focusing on maternal health targeting, HIV test schema alignment, data quality, and automated data ingestion. These changes improve data validity, historical integrity, and reporting reliability, enabling more accurate public health targeting and timelier insights for program decisions.

October 2025: Delivered critical public health data improvements across two repositories, strengthening data access controls, expanding event and vaccination data capabilities, and enabling Google Sheets-based CDI ingestion. Also completed a targeted cleanup of protocol scaffolding to reduce technical debt. These changes delivered improved data reliability, governance, and automation for public health analytics, with demonstrations of data modelling, access-control design, and pipeline integration.

September 2025 monthly summary for prefeitura-rio/queries-rj-sms: Delivered core data-model enhancements for IplanRio integration and WhatsApp provisioning, strengthenedFicha A data quality, and expanded PIC protocol event tracking. The work enabled more reliable patient data, streamlined data sourcing with dbt ref, and improved operational readiness for WhatsApp-based communications and analytics.

August 2025 focused on expanding API coverage, stabilizing data contracts, and refining the data pipeline for prefeitura-rio/queries-rj-sms. Delivered multiple new health-condition models for the Vitacare API, implemented initial and evolved phone validation for WhatsApp IplanRio, and completed a set of quality and reliability improvements across data models, schemas, and configurations. Result: richer health data capture, improved data quality, and a more scalable, maintainable codebase with standardized naming and schemas, reducing future maintenance and enabling faster onboarding for downstream teams.

July 2025 – Prefeitura Rio / Queries RJ-SMS: Delivered core data-model and API improvements with measurable business value. Key accomplishments include introducing the APS indicators model with incremental materialization to capture historical execution data; restructuring Ficha A models to support continuidade and histórico representations; adding Prontuario Vitacare API models (derived from atendimento contínuo) and wiring them into dbt_project.yml to broaden API-derived analytics; fixing data_partition handling for atendimento_continuo (datetime casting and fim_atendimento alignment) and centralizing partition filters via bruto_atendimento CTE across related models; implementing comprehensive string/date casting across models for data type consistency. These changes improve data reliability, enable historical analytics, broaden API coverage, and improve ETL performance.

June 2025: Implemented a privacy-focused anonymized dataset for the cie dashboard, enabling daily processing of ficha_a data in prefeitura-rio/queries-rj-sms. Delivered a privacy-preserving data model and the SQL logic for the new table within the cie dashboard context, plus automated daily processing via a new project configuration tag. These changes reduce data risk, accelerate time-to-insight, and support safer, near-real-time dashboards for stakeholders.