Enriching postal addresses with Elastic stack

Played 8 times
Videos 1
First Apr 2019
Last Nov 2023

Enriching postal addresses with Elastic stack

Come and learn how you can enrich your existing data with normalized postal addresses with geo location points thanks to open data and BANO project .

Most of the time postal addresses from our customers or users are not very well formatted or defined in our information systems. And it can become a nightmare if you are a call center employee for example and want to find a customer by its address. Imagine as well how a sales service could easily put on a map where are located the customers and where they can open a new shop…

Let’s take a simple example:

{
  "name": "Joe Smith",
  "address": {
    "number": "23",
    "street_name": "r verdiere",
    "city": "rochelle",
    "country": "France"
  }
}

Or the opposite. I do have the coordinates but I can’t tell what is the postal address corresponding to it:

{
  "name": "Joe Smith",
  "location": {
    "lat": 46.15735,
    "lon": -1.1551
  }
}

In this live coding session, I will show you how to solve all those questions using the Elastic stack.

Title

Enriching postal addresses with Elastic stack

Abstract

> Come and learn how you can enrich your existing data with normalized postal addresses with geo location points thanks to open data and [BANO project](http://bano.openstreetmap.fr/data/).

Most of the time postal addresses from our customers or users are not very well formatted or defined in our information systems. And it can become a nightmare if you are a call center employee for example and want to find a customer by its address.
Imagine as well how a sales service could easily put on a map where are located the customers and where they can open a new shop…

Let's take a simple example:

```json
{
  "name": "Joe Smith",
  "address": {
    "number": "23",
    "street_name": "r verdiere",
    "city": "rochelle",
    "country": "France"
  }
}
```

Or the opposite. I do have the coordinates but I can't tell what is the postal address corresponding to it:

```json
{
  "name": "Joe Smith",
  "location": {
    "lat": 46.15735,
    "lon": -1.1551
  }
}
```

In this live coding session, I will show you how to solve all those questions using the Elastic stack.

Enrichir les adresses postales avec la suite Elastic

Venez apprendre comment enrichir vos données existantes avec des adresses postales normalisées et des points de géolocalisation grâce à l’open data et au projet BANO .

La plupart du temps, les adresses postales de nos clients ou utilisateurs ne sont pas très bien formatées ou définies dans nos systèmes d’information. Et cela peut devenir un cauchemar si vous êtes un employé de centre d’appel par exemple et que vous voulez trouver un client par son adresse. Imaginez également comment un service commercial pourrait facilement mettre sur une carte où sont situés les clients et où ils peuvent ouvrir un nouveau magasin…

Prenons un exemple simple :

{
  "name": "Joe Smith",
  "address": {
    "number": "23",
    "street_name": "r verdiere",
    "city": "rochelle",
    "country": "France"
  }
}

Ou l’inverse. J’ai les coordonnées mais je ne peux pas dire quelle est l’adresse postale correspondante :

{
  "name": "Joe Smith",
  "location": {
    "lat": 46.15735,
    "lon": -1.1551
  }
}

Dans cette session de live coding, je vous montrerai comment résoudre toutes ces questions en utilisant la suite Elastic.

Title

Enrichir les adresses postales avec la suite Elastic

Abstract

> Venez apprendre comment enrichir vos données existantes avec des adresses postales normalisées et des points de géolocalisation grâce à l'open data et au [projet BANO](http://bano.openstreetmap.fr/data/).

La plupart du temps, les adresses postales de nos clients ou utilisateurs ne sont pas très bien formatées ou définies dans nos systèmes d'information. Et cela peut devenir un cauchemar si vous êtes un employé de centre d'appel par exemple et que vous voulez trouver un client par son adresse.
Imaginez également comment un service commercial pourrait facilement mettre sur une carte où sont situés les clients et où ils peuvent ouvrir un nouveau magasin…

Prenons un exemple simple :

```json
{
  "name": "Joe Smith",
  "address": {
    "number": "23",
    "street_name": "r verdiere",
    "city": "rochelle",
    "country": "France"
  }
}
```

Ou l'inverse. J'ai les coordonnées mais je ne peux pas dire quelle est l'adresse postale correspondante :

```json
{
  "name": "Joe Smith",
  "location": {
    "lat": 46.15735,
    "lon": -1.1551
  }
}
```

Dans cette session de live coding, je vous montrerai comment résoudre toutes ces questions en utilisant la suite Elastic.

Resources

Useful resources related to this talk.

© 2010 - 2026 David Pilato

🔍 Search is powered by QueryBox. Just hit CTRL+K or CMD+K to start searching.

⚙️ Generated from 🇫🇷 with ❤️ on Fri Jan 9, 2026 at 12:32:30 UTC

🌱 Powered by Hugo with theme Dream.

Details

I discovered Elasticsearch project in 2011. After contributed to the project and created open source plugins for it, David joined elastic the company in 2013 where he is Developer and Evangelist. He also created and still actively managing the French spoken language User Group. At elastic, he mainly worked on Elasticsearch source code, specifically on open-source plugins. In his free time, he likes talking about elasticsearch in conferences or in companies (Brown Bag Lunches AKA BBLs ). He is also author of FSCrawler project which helps to index your pdf, open office, whatever documents in elasticsearch using Apache Tika behind the scene.

Who am I?

Developer | Evangelist at elastic and creator of the Elastic French User Group . Frequent speaker about all things Elastic, in conferences, for User Groups and in companies with BBL talks . In my free time, I enjoy coding and deejaying as DJ Elky , just for fun. Living with my children in Cergy, France.

Social Links