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Why are clients that have been deleted, or exited, still showing up in my reports?

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< Back is designed to build a cumulative record for clients that are enrolled in projects, over time. If there are gaps in the data, then the reports may not be complete. The following scenario illusatrates how this works:

  • Client “Jane Smith” is enrolled into Project A on September 1, 2015.
  • Staff run a data export for an APR that runs from January 1, 2015 to December 31, 2015. The data export and the report are over the same date range. Joe Smith appears in the report.
  • Jane Smith exits the project on January 15, 2016.
  • Staff run a new data export for the project for the day of the Point in Time Count – January 25, 2016. Jane Smith is still showing up on the report, even though she left ten days prior.

Why did this occur?
This happened because the record that Jane Smith exited was never imported into The system is still seeing the enrollment record from September 1, 2015 but never received an updated record showing she exited on January 15, 2016.

How can I tell what data has been loaded for a project and what the gaps are?
The Home Page of HomelessData shows the date range(s) for project level data for all of the projects that each user has access to. The red bars indicate that there is a gap, although if there is a one day gap, the bar won’t be red).  The date is revealed by hovering over the bar. By selecting the button for “Show Projects with Gaps Only,” a user can filter their projects to show just those that are missing data.


The date range of the data imports is displayed on the Data Management screen so the user can determine if the data required for a report has been loaded into the system.

Similarly, if a client record was deleted from one dataset but not another, the client may still show in in a report.

There are many reasons why an organization or region would benefit from maintaining a complete picture for each project and for each client, and a data export for a single day doesn’t provide much value and can unintentionally create issues such as the one described above. To prevent this, we encourage administrators to pre-populate with data starting on October 1, 2012 to present. While this initial export may take a while longer, each subsequent refresh can cover just the interval of time since the last update. allows users to also import discreet data sets. This may be a good option if you are missing clients when the report is run over all data for a project.