Analytics Platform & DHIS2

Analytics Platform is an open-source data integration and analytics layer developed by BAO Systems that can be cloud-based or deployed locally on-premises. It integrates DHIS2 HMIS data with HR, supply chain, finance, and other health data sources via no-code connectors, centralising data for real-time cross-system analytics, AI-powered natural text queries, and Superset dashboards embedded directly within DHIS2.

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About Analytics Platform

Analytics Platform helps users integrate, transform, and analyse data from multiple systems. It uses a modern ELT (Extract, Load, Transform) architecture – loading raw data into a scalable warehouse before transformation – replacing fragile ETL pipelines. The platform is designed to be accessible to users ranging from non-technical programme staff through to data scientists, reducing the manual burden of exporting, transforming, and running reports, so teams can focus on generating actionable insights.

Key capabilities:

No-code connectors: Turnkey pipelines to DHIS2, CommCare, ODK, iHRIS, Kobo, FHIR, BHIMA, PostgreSQL, MySQL, Google Sheets, Azure, Amazon S3/Redshift and more – no custom code required
Natural text queries: Users ask questions in plain language; Analytics Platform converts to SQL and returns real-time results without needing SQL or Python expertise
Embedded BI in DHIS2: The Super BI web app embeds Apache Superset dashboards directly inside DHIS2 without duplicating data
DHIS2-to-Power BI DAX: Automatically converts DHIS2 indicator expressions to DAX, resolving the standard challenge of recreating DHIS2 calculations in Power BI
Conversational analytics: The Convo app lets users chat with DHIS2 data in natural text, with AI generating visualisations and dashboards on demand
Python & R scripting: Integrated environments for advanced transformation, statistical computation, predictive modelling, and machine learning
Data quality notifications: Automated checks with instant alerts for outliers and inconsistencies
Flexible deployment: AWS, Azure, GCP, on-premise, or BAO Systems managed SaaS. Open-source and self-hostable.
BI tool connectivity: Connect Power BI, Tableau, or any SQL-compatible tool directly to Analytics Platform’s data warehouse
Secure by design: Built to inherit DHIS2 roles and security permissions, with enhanced audit trails, logging, and data encrypted in transit and at rest.
Public dataset library: Built-in access to WHO Global Health Observatory, World Bank, UN demographic and population datasets for data triangulation

Analytics Platform is a Strategic DHIS2 Technology Partner.

DHIS2 use case

DHIS2 is widely used for routine health data collection but often exists in isolation, disconnected from the HR, supply chain, financial, and survey data programme managers need for fully-informed decisions. Analytics Platform acts as an integration and analytics layer alongside DHIS2, pulling data from DHIS2 and other systems into a unified warehouse and data lake for combination, transformation, and analysis. Results and aggregated analytics can be pushed back into DHIS2, and dashboards embedded directly within the DHIS2 interface. Users never leave their existing system.

Efficiency: Reducing manual labour and staff time

System integration eliminates data silos that require manual intervention. Health staff traditionally spend significant hours exporting data from platforms like Excel or independent databases, manually cleaning and reformatting into a single report. Automating the ETL process through Analytics Platform or custom API connectors removes this burden entirely, redirecting staff time from administration to analysis and programme delivery.

Insight: Enhanced visibility for decision-making

A centralised system provides a single source of truth across the health landscape. When service delivery data (HMIS) is combined with human resource data (iHRIS) and supply chain metrics (LMIS), decision-makers can identify correlations previously invisible in siloed systems. An official can move beyond seeing a drop in immunisation rates to pinpointing whether it was caused by a vaccine stockout or a staffing shortage at a specific facility, enabling targeted interventions based on a complete picture.

Integrity: Reducing data quality errors

Manual data entry and cross-platform manipulation are primary sources of human error. Analytics Platform establishes automated validation rules and standardised data definitions across all connected systems. With data flowing directly between systems without human touchpoints, the risk of transcription errors, duplicate entries, and inconsistent naming conventions is substantially reduced, ensuring policy decisions are based on accurate, verified information.

Velocity: Improving data timeliness

Fragmented systems produce reporting lags where data is weeks or months old before it reaches central planners. Analytics Platform enables near-real-time availability: automated ingestion schedules update dashboards daily or weekly, allowing health officials to respond rapidly to emerging trends such as disease outbreaks or commodity shortages. This shift from retrospective reporting to proactive management is critical for a resilient health infrastructure.

DHIS2 Performance

Analytics Platform addresses common DHIS2 performance issues (slow dashboards, out-of-memory errors, large data volumes) by serving as a scalable extension. It connects directly to the DHIS2 database for faster extraction and more efficient processing of large datasets, including millions of records. Users can query data within an integrated warehouse for advanced analytics while reducing load on the core DHIS2 system. Analytics Platform also supports archiving and clean-up of obsolete aggregate and tracker data from DHIS2, while keeping that data accessible for historical analysis.

Platform-specific capabilities:

Full data extraction: The DHIS2 connector pulls metadata, aggregate data, events, and tracked entities into an analytics-optimised warehouse schema
Advanced analytics: Supports cross-program, tracked entity relationship, and cohort analytics in real time, while preserving DHIS2 access control
Embedded dashboards: Super BI embeds Superset visualisations inside DHIS2 – users work within their existing DHIS2 instance and user accounts, with no data duplication
Conversational access: The Convo app for DHIS2 lets non-technical staff query programme data in plain language with AI-generated visualisations
Power BI DAX conversion: DHIS2 indicator expressions automatically converted to DAX, enabling accurate DHIS2 reporting in Power BI
Write-back to DHIS2: Data aggregated or transformed in Analytics Platform can be pushed back into DHIS2 via destinations
Cross-system triangulation: Analytics Platform connects DHIS2 with iHRIS (human resources), LMIS (supply chain), CommCare, ODK, and public datasets, allowing decision-makers to analyse DHIS2 service data alongside staffing, stock, and population data in a single view

Real-world example

Strengthening Health Systems in Senegal

The challenge: The primary challenge in Senegal was the absence of a centralized health information system, which prevented the Ministry of Health and Social Action (MSAS) from utilizing data to improve service delivery. Historically, the national health system was highly fragmented, with data collected across thirteen different, non-communicable systems and a multiplicity of software tools. This lack of integration made it impossible for the Ministry to gain a comprehensive overview of the health landscape or perform evidence-based decision-making across all health services.
The solution: BAO Systems worked to integrate disparate health information subsystems into a centralized data repository. The team began by evaluating the existing landscape to analyze the interoperability capabilities of each subsystem and conducted focus groups with stakeholders to document specific user needs and data utilization goals. BAO Systems introduced an enterprise health information system architecture to facilitate Health Information Exchange (HIE) between systems such as SNIS and iHRIS. A key part of this solution involved deploying the Analytics Platform within the Ministry’s data center and hosting in-person workshops to develop an integrated analytics plan and an interoperability roadmap.
The outcome: The project successfully established a system integration and a validated roadmap for future interoperability. By centralizing data from previously disconnected systems, BAO Systems enabled the Ministry of Health to generate actionable insights through customized dashboards. These tools now allow officials to identify which health facilities are meeting staffing standards, monitor over- or under-staffing relative to patient volume, and track essential drug stocks to predict and prevent potential shortages. This transformed the fragmented data landscape into a reliable, accountable system that supports improved health service accessibility throughout Senegal.

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Strengthening Health Systems in the Democratic Republic of Congo

The challenge: A major barrier to progress was the fragmentation of health information; data was siloed across multiple independent platforms, including the national health management information system (SNIS), human resources records (iHRIS), and supply chain management systems (BHIMA). This lack of integration made it difficult for officials to access a comprehensive view of health system performance or use raw data effectively for routine decision-making.
The solution: BAO Systems implemented a strategy focused on system interoperability and user-centric design. After conducting rapid user research in Kasai province to identify priority needs, the engineering team developed custom connectors for the iHRIS and BHIMA platforms. These connectors allowed for the seamless ingestion of human resource and supply chain data into a centralized warehouse alongside routine health service data. To make this information actionable, the team piloted Analytics Platform and collaborated with Ministry of Health staff through district-level workshops to develop an integrated analytics plan. This collaborative effort ensured that the resulting data visualizations were aligned with the specific questions and requirements of local health administrators.
The outcome: The project resulted in a unified data ecosystem that supports the Congolese government’s universal health coverage strategy and national health policy. By successfully enabling the integration of service delivery, staffing, and commodity data, the program provided health officials with a series of interactive Power BI dashboards. These tools display key performance metrics in a clear, visual format, empowering decision-makers to manage resources more effectively. Ultimately, these improvements in data access and analysis serve to strengthen the health system’s ability to improve sexual and reproductive health outcomes for vulnerable populations across the region.

Supporting resources

Analytics Platform Documentation:
Videos: