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In this tutorial, you will learn how to set up a data export. Each export si defined in the export object.
| Table of Contents |
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What you'll create
This is the export window, where you can download the export in a CSV file.
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Customers export
Let's have a look at our customers customers dataset one more time. We will identify the properties that will be included in our export. Note that all active filters and the map selection are counted in the exports.
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The properties we want to include are: customer_id, address, sex and age_group.
Name | Title | Data type |
|---|---|---|
| Customer ID | integer |
| Neighborhood code | string |
| Customer's city | string |
| Customer's address | string |
| Customer's sex | string |
| Customer's age group | string |
| Address latitude | latitude |
| Address longitude | longitude |
The export object will look like this:
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Customers export syntax
| Code Block |
|---|
{
"name": "customers_export",
"type": "export",
"title": "Customers export",
"content": {
"properties": [
"customers.customer_id",
"customers.address",
"customers.sex",
"customers.age_group"
]
}
} |
Add this export object to the project using addMetadata. Now we just need to add the export reference to the business_overview_view object.
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Business overview view excerpt
| Code Block | ||
|---|---|---|
| ||
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"mapOptions": {
"center": {
"lat": 49.203,
"lng": 16.606
},
"zoom": 12,
"tileLayer": "mapbox"
},
"exports": [
{
"export": "/rest/projects/$projectId/md/exports?name=customers_export"
}
]
},
"accessInfo": {
... |
Before we perform the export, we have to apply the required filter first.
Applied histogram filter on the transaction_size property
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Also, don't forget that the map window should contain all available areas.
The export is available after clicking the Menu button in the top left corner (
), and selecting Export.
...
Select Customers Select Customers export and hit Export.
The selected columns, as well as metric results will be present in the customers_export.csv file.
Stores export
This is the stores dataset we've added in the previous tutorial.
Identifier | Title | Data type |
|---|---|---|
| Store ID | integer |
| Store address | string |
| Store type | string |
| Opening hours | string |
| Monthly rent | integer |
| Contact email | string |
| Store web link | string |
| Designated parking lot | string |
| Number of employees | integer |
| Store's latitude | latitude |
| Store's longitude | longitude |
We won't put any filters on this export and we'll export these properties: store_id, address, store_type, contact.
It is possible to include properties from other datasets in an export. We will include some properties from datasets of the Administrative units dimension we've added in one of the previous tutorials.
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cast_obec_dwh.nazev- the city district where the store is locatedokres_dwh.nazev- name of the countykraj_dwh.nazev- name of the region
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Stores export syntax
| Code Block |
|---|
{
"name": "stores_export",
"type": "export",
"title": "Stores export",
"content": {
"properties": [
"stores.store_id",
"stores.address",
"stores.store_type",
"stores.contact",
"cast_obec_dwh.nazev",
"okres_dwh.nazev",
"kraj_dwh.nazev"
]
}
} |
Add the object using addMetadata and add the export reference to the business_overview_view object.
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Business overview view excerpt
| Code Block | ||
|---|---|---|
| ||
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"mapOptions": {
"center": {
"lat": 49.203,
"lng": 16.606
},
"zoom": 12,
"tileLayer": "mapbox"
},
"exports": [
{
"export": "/rest/projects/$projectId/md/exports?name=customers_export"
},
{
"export": "/rest/projects/$projectId/md/exports?name=stores_export"
}
]
},
"accessInfo": {
... |
...
You can see that the stores_export.csv contains all six stores, with respective results of all metrics in all city districts.
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| Info | icon | false
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That's it! In the ...