Digital transformation is at the heart of the regions: digitization of services, automation of processes, interoperability of systems. Expectations are high. Yet many projects stagnate or fail to deliver the expected benefits.
The main obstacle is not technology, but data quality: dispersed databases, duplication, data entry errors, lack of shared repositories.
HR, transport, environment, social aid: every public policy depends on reliable data. If they are inaccurate, decisions are distorted and indicators lose their value.
This is no longer just a technical issue. It's about governance, transparency and public efficiency.
👉 To discover our global approach, see also page dedicated to data quality for the public sector.
In several regions, the merger of local authorities led to the creation of inconsistent HR databases: duplicate agents, heterogeneous job titles, incomplete data. These anomalies complicated administrative management, payroll and regulatory compliance.
Thanks to a no-code platform, HR teams were able to automate duplicate detection, consolidate agent data and re-establish a reliable repository.
The teams now have a clear, secure repository, with fewer errors, more reliable HR data and greater autonomy from the IT department.
In the transport sector, an analysis of GTFS flows revealed the absence of stops on a TER line between two major cities. These omissions were causing inconsistencies in mobility applications, disorienting users and damaging the service's image.
The Region set up an automated GTFS flow control system to detect anomalies (orphan stops, inconsistent timetables) and alert users in real time. A collaborative space has been opened up to operators to keep a shared database up to date.
This project has improved the quality of transport data, reduced complaints and enhanced the reliability perceived by citizens.
A number of regions were experiencing the distribution of erroneous pollution alerts, due to poorly calibrated sensors or unfiltered noisy data. These false alerts affected public communication and inter-institutional coordination.
The integration of a quality control engine enabled measurements to be compared with national thresholds, abnormal deviations to be identified, and business rules to be set to filter out aberrant data.
The Region has thus restored the reliability of its environmental indicators, strengthened the confidence of its partners (ARS, prefectures) and secured the publication of its data in open data.
Our white paper brings together 12 case studies from the field. You'll discover
📘 This guide is aimed at public decision-makers who want to structure concrete data governance.
👉 Download the white paper - Data quality for regional transformation
Unlike traditional technical solutions, Tale of Data enables business units (HR, finance, transport, environment, etc.) to :
This autonomy is transforming the way public services manage data.
The success of a digital transformation project depends directly on the reliability of the data available. This is a prerequisite for steering, optimizing, securing and anticipating.
The white paper Data Quality for the Transformation of French Regions brings together 12 concrete, detailed and actionable case studies, to help you structure your approach right away.
📘 D ownload the white paper - Transformation des Régions
📎 Do you work in a Conseil Départemental? See also our article dedicated to data quality in the départements.