The blog post outlines the process of using the Elastic Stack, specifically Logstash, to enrich postal address data in France by leveraging the Base d'Adresses Nationale (BANO) dataset. The author describes the challenges of incomplete and poorly formatted address data, which complicates tasks like mapping customer locations and retrieving addresses from geographic coordinates. To address these issues, the post discusses the drawbacks of using external services like Google Maps API, such as latency and data privacy concerns, and instead proposes a local solution using BANO, an open dataset under the OpenStreetMap umbrella. The post details steps to download BANO CSV files for French departments, parse and load the data into Elasticsearch, and set up index templates to handle address data efficiently. Additionally, it explains the use of custom analyzers for address normalization and the creation of Logstash pipelines to transform and store the data. The result is a searchable, enriched dataset that can be visualized using Kibana, providing insights into address distribution and enabling tasks such as address correction and transformation.