Good practices integrating DHIS2 with BI tools for advanced analytics and local ownership

This abstract has been accepted at the 2024 DHIS2 Annual Conference


Good practices integrating DHIS2 with BI tools for advanced analytics and local ownership

There is a growing interest in the DHIS2 community about connecting DHIS2 with other analytics platforms and business intelligence tools like PowerBI, Tableau, Superset, etc. What is the rationale for choosing other tools to perform visualizations and analysis?

In some cases these decisions are driven by a lack of knowledge about the analytics tools of DHIS2; or by preferences for user interfaces or visualizations. However as data size and complexity increases, DHIS2 may not always be the most appropriate tool for performing certain transformations and calculations; although, is typically the main source for key data.

Based on the growing interest there are several proprietary solutions using proprietary infrastructure. In SolidLines we believe that every organisation is owner of their data, so the data and its transformation should live in the organisation infrastructure. Moreover, expanding the knowledge of integrations between DHIS2 with BI tools can be beneficial for the community.

We would like to highlight several approaches about data access and system integration for analytics.

  • Accessing DHIS2 data - Web API: Accessing RAW data using the most common endpoints (dataValueSets, events, trackedEntityInstances) with relevant filters (lastUpdated, programs,…)
  • Line Listing reports for tracker data and visualizations for aggreated: Creating different type of reports in DHIS2 that can be downloaded using the API (/visualizations, /eventReports)
  • Data base: Accessing directly the tables inside the DHIS2 database to download the trackedEntityInstances, events and datavalues Integration between DHIS2 and BI tools
  • Direct connection: Most of the BI platforms contains tools that allows direct connections with externals APIs (like the DHIS2 API) and external databases (like DHIS2 database)
  • Using a Data Warehouse (DWH): DWHs are the main data source for BI tools. This approach consists in having a DWH between DHIS2 and the BI tool. The DWH will store the data coming from DHIS2 and act as the data source for a BI tool.

In Solidlines we have several years of experience building analytic ecosystems for organisations. They are mainly open source and focus on local maintenance and support. We would like to share our knowledge with the community, presenting some demos (eg. exposing tracker data to different BI tools), discussing the different alternatives and approaches to apply, and always based on the complexity of the use cases and the technical capacity of the organisations we serve. We also would like to discuss some potential improvements in DHIS2 to facilitate integrations with BI tools.

Primary Author: Carlos Tejo-Alonso


Keywords:
DHIS2, Data Warehouse, advances analytics, local ownership

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