A four-page Power BI project examining internal displacement and return movements across Sudan using public data from the IOM Displacement Tracking Matrix (DTM) Sudan.
The dashboard is based on the IOM DTM Sudan IDPs and Returnees Snapshot 007, dated 30 June 2026, and is designed to support geographic comparison of displacement and return caseloads across Sudan's states and localities.
This project provides a structured analytical view of the reported internal displacement and return situation in Sudan as of 30 June 2026.
The dashboard focuses on:
- Internally displaced people (IDPs)
- IDP households
- Returned individuals
- Returnee households
- State-level displacement and return pressure
- Locality-level caseload distribution
The objective is to make the IOM DTM snapshot easier to explore and interpret through an interactive Power BI report.
The dashboard is designed to answer questions such as:
- Which states report the largest internally displaced populations?
- Which states report the largest numbers of returned individuals?
- How do displacement and return caseloads compare across states?
- Which localities account for the largest reported IDP caseloads?
- Which localities report the largest return movements?
- Where is displacement pressure concentrated geographically?
- What does the 30 June 2026 snapshot show about the distribution of internal displacement and returns across Sudan?
Provides a high-level summary of the Sudan displacement and return situation.
Key indicators include:
- Total internally displaced people
- Total IDP households
- Total returned individuals
- Total returnee households
- State coverage
- Locality coverage
The page provides a national-level view before moving into more detailed geographic analysis.
Compares displacement and return caseloads across Sudan's states.
The page is designed to identify:
- States with the largest IDP populations
- States with the largest return movements
- Differences between displacement and return pressure
- Geographic concentration of reported caseloads
A key visual is the State Pressure Matrix, which uses a diverging layout:
- IDP caseloads extend in one direction
- Returned-individual caseloads extend in the opposite direction
This allows displacement and return pressure to be compared directly for each state without relying on overlapping bubbles.
IDP-household information is also available as supporting context.
Provides more detailed analysis at the locality level.
Users can explore:
- Locality-level IDP populations
- Locality-level return movements
- Ranked caseloads
- Geographic concentration within selected states
The page allows users to move from national and state-level analysis into more detailed local-level exploration.
Documents:
- Data source
- Reporting date
- Geographic grain
- Metric definitions
- Analytical assumptions
- Limitations
- Interpretation guidance
The purpose of this page is to make the analytical process transparent and prevent the dashboard from being interpreted beyond what the source data supports.
International Organization for Migration (IOM)
Displacement Tracking Matrix (DTM) Sudan
Dataset:
IDPs and Returnees Snapshot 007
Reporting date:
30 June 2026
Source:
The dashboard is structured geographically around:
- State
- Locality
It represents a single operational snapshot dated 30 June 2026.
The dataset is therefore not structured as an origin-by-year time series.
The dashboard reports:
- Internally Displaced People (IDPs)
- IDP Households
- Returned Individuals
- Returnee Households
These are the primary population measures used throughout the report.
The source snapshot covers:
- 18 states
- 185 localities
As reported in the IOM DTM Sudan snapshot dated 30 June 2026:
- 8,685,273 internally displaced people
- 1,742,414 IDP households
- 4,649,056 returned individuals
- 928,168 returnee households
- 18 states
- 185 localities
These values represent the operational estimates reported in the source snapshot.
The dashboard uses descriptive analysis to compare the geographic distribution of displacement and return caseloads.
The analysis includes:
- National-level aggregation
- State-level comparison
- Locality-level ranking
- Displacement-versus-return comparison
- Geographic filtering
- Caseload concentration analysis
The dashboard does not attempt to estimate causal relationships or predict future displacement.
This dashboard is an analysis of internal displacement and return movements recorded by IOM DTM Sudan.
It is not a refugee-status dashboard.
IOM's Displacement Tracking Matrix is used as a source of mobility and displacement information.
The dashboard does not treat IOM DTM data as refugee-status determinations and does not imply that IOM grants or recognizes refugee status.
Terms such as refugees, asylum-seekers, refugee recognition, origin-year observations, or cross-border refugee status are not used as analytical categories in this report.
Where a combined population figure is displayed, it is calculated as:
Reported IDPs + Reported Returned Individuals
This is a dashboard-level analytical sum intended to summarize the populations represented in the selected snapshot.
It should not be interpreted as:
- A historical cumulative displacement total
- A count of unique individuals over time
- A national population estimate
- A measure of all displacement-affected people in Sudan
IOM DTM figures are operational estimates and may be revised as:
- Field verification improves
- Access conditions change
- New information becomes available
- Previously reported figures are updated
Additional limitations include:
- The dashboard represents a single snapshot, not a historical time series.
- Reported figures should not be interpreted as permanent or final population counts.
- State and locality comparisons are descriptive and do not measure humanitarian severity.
- Larger caseloads do not automatically imply greater humanitarian need.
- The dashboard does not measure access constraints, protection risks, service availability, or response capacity.
- Geographic totals reflect the structure and definitions of the source dataset.
The dashboard should therefore be used as a descriptive analytical tool rather than as a substitute for formal humanitarian needs assessments.
The project was reviewed to ensure consistency between:
- Dashboard visuals
- KPI values
- State-level totals
- Locality-level data
- Metric definitions
- Data-source documentation
- Methodology statements
The methodology was specifically aligned with the Sudan IOM DTM dataset so that the documentation accurately reflects the data used in the report.
- Power BI Project (
.pbip) format - Power Query data preparation
- DAX measures
- Interactive state and locality filtering
- Geographic comparison
- State-level pressure analysis
- Ranked locality analysis
- Dedicated methodology and source documentation
IOM Displacement Tracking Matrix (DTM) Sudan
IDPs and Returnees Snapshot 007 — 30 June 2026
Khalid SaadAldin Yahia
Data Analyst | Power BI | Python | SQL | Excel