en
Get Started

namR store

This plugin provides recipes to call the namR store API

Plugin information

Version 1.0.0
Author namR
Released 2021-08-03
Last updated 2021-08-03
License Apache Software License
Source code Gitlab
Reporting issues Gitlab

namR store – Data enrichment plugin

Whether you are a business analyst or data engineer, this plugin recipe offers an easy access to the namR store API and data
In this documentation we are sharing all the needed information to work with this plugin recipe :
  • Requirements
  • Deployment
  • Access Token
  • Getting started
  • namR store
  • Contributions
Need support ? Contact [email protected]

Requirements

This plugin has been developped under DSS v7.0.2.
  • DSS v7.0.X or above
  • Administrator right
  • Access token to namR store (see below)

Access token

Our sales team will be glad to get you an acces token to namR store (trial ou premium) [email protected]
In the context of namR store, a token might have three scopes restrictions:
  • Geographical scope, eg. one municipality – Clichy insee code 92024
  • Data scope: data related to a specific entity, eg. to building characteristics: building construction period, building height
  • Limitations and quotas

Getting started

1. Flow

At recipe creation, you will be ask to provide 3 datasets:
  • 1 input dataset
  • 2 output datasets
Before running the JOB, ACCESS TOKEN must be filled in the settings.

2. Datasets description

Input dataset

This part describes input dataset provided by users.

It requires at least two fields :

Fields to provide

Output datasets

This part describes the datasets created by this plugin recipe
Data

This dataset provides all fields available for each row of the input dataset. It, also, gives extra informations an API calls (query and status) for each row processed.

Data available
Metadata
This dataset provides meta informations on delivered fields.
Metadata available

namR store

Each row found in the input dataset are processed by the namR store engine with the following pipelines :
Step1: Geocoding
Geocoding is the process of geolocalized a text-based described of a location (address or place name).
For each row, our in-house geocoder will geolocalized your address and provide an internal unique identifier.
Null values are returned for addresses out of the token geographical scope. (see above)
Step2: Link between addresses and entities
Then each address is linked to the requested entities (eg. building).
Step3: Fetch informations
Token data scope are returned for each entity identified.
eg. building -> building height, building construction period …
Step4: Return information
Each information available on the data scope will be returned on a denormalized way.
The above description provide a very simple overview of the namR store engine.

Get the Dataiku Data Sheet

Learn everything you ever wanted to know about Dataiku (but were afraid to ask), including detailed specifications on features and integrations.

Get the data sheet