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Etienne Burdet

Software Engineer, Opendatasoft

After an early career in energy and environmental research in both academia and urban planning agencies, Etienne is now a software engineer at Opendatasoft. He primarily works on data visualization and front-end application topics.

He has worked on projects related to solar power plants, waste sorting in train stations, and heat islands in Bahrain and Morocco. He is currently focused on projects such as the Frais & Local app and the ODS Studio data visualization tool.

Frais et local EN
Product Open data & transparency
Frais et Local: How we developed the French Ministry of Agriculture’s app
Etienne Burdet
10 May 2022
We’ve all seen the formula, popularized by Airbnb and Google Maps, with a list on one side, a map on the other, a search field, and a geolocation button. How can you create your own version, based on sharing your data?
Product
Geographical Referentials: Data Quality in Stages
Etienne Burdet
05 January 2021
If you’ve spent time roaming through our Data hub, data.opendatasoft.com, you know how vast and comprehensive our catalog of datasets is. Learn our best practices.
Basemap - header
Data intelligence & reporting Product
What Is a Basemap and How to Choose the Best One for Your Data?
Etienne Burdet
03 September 2015
Without a basemap, your geographical data has little value. This blog post walks you through the definition of a basemap and how to choose one for your data platform.
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The state of data democratization: lessons from our 2025 study Uncategorized
The state of data democratization: lessons from our 2025 study

Organizations have never relied so much on data, within their operations, strategies and decision-making. However, our latest research finds gaps between company objectives for data sharing and the reality on the ground.

Building effective teams to increase data consumption at scale Data access
Building effective teams to increase data consumption at scale

Chief Data Officers need to put in place the right skills, resources and structures to share data at scale. Based on new Gartner research, we look at the options for creating effective data teams to meet local and central needs.

Delivering AI success through seamless access to actionable and machine readable data Data access
Delivering AI success through seamless access to actionable and machine readable data

High quality data is at the heart of successfully training and deploying AI algorithms and agents. Our blog explains how organizations can ensure that they are sharing easily actionable, machine readable data with AI through data products and data product marketplaces