Video test

Updated on

Aug 17, 2023

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Code Block

Some code here

const value = 0;

{
  "description": "this is a json format with correct syntax highlight",
  "Version": "23Q1"
}

Table

Recipe	Data source
Paid Ads	```paid_ads__basic_performance```

Recipe	Data source
Paid Ads	```paid_ads__basic_performance```

Recipe	Data source
Paid Ads	```paid_ads__basic_performance```

Info panels

{% docs-informer info %}

To better understand the ```Improvado Marketing Common Data Model``` and how it works, you can check the Improvado MCDM Overview.

{% docs-informer-end %}

{% docs-informer warning %}

To better understand the ```Improvado Marketing Common Data Model``` and how it works, you can check the Improvado MCDM Overview.

{% docs-informer-end %}

{% docs-informer error %}

To better understand the ```Improvado Marketing Common Data Model``` and how it works, you can check the Improvado MCDM Overview.

{% docs-informer-end %}

{% docs-informer info %}

Improvado doesn’t perform any edit, create, or delete operations. To ensure the security of your Google Ads account, we recommend creating a new user or updating an existing one with read-only access to be used for data extraction:

{% docs-informer-end %}

{% docs-informer info %}

Improvado doesn’t perform any edit, create, or delete operations.

sql_field_name
```spend / 1.15```
```'FB'```
```''```
```0.0```
```CASE WHEN campaign_name like '%IG%' THEN 'IG Campaign' ELSE campaign_name END```

{% docs-informer-end %}

Nested lists

Unordered list

Step 1
Step 2
~Step 2.1.
~Step 2.2. ```client_id```
~~Step 2.2.1.
~~Step 2.2.2.
~~Step 2.2.3.
~Step 2.3.
~Step 2.4.
Step 3.
~Step 3.1.
Step 4.
Step 5. ~C:/path
~Step 5.1. ~C:/path

Ordered list

Step 1
Step 2
~Step 2.1.
~Step 2.2. ```client_id```
~~Step 2.2.1.
~~Step 2.2.2.
~~Step 2.2.3.
~Step 2.3.
~Step 2.4.
Step 3.
~Step 3.1.
Step 4.
Step 5. ~C:/path
~Step 5.1. ~C:/path

Custom list for intstruction steps

Step 1. Step 1

Step 2. Step 2

Step 2.1. Step 2.1

Step 3. Step 3

Link cards

{%docs-links%} [ { "url": "/docs/available-attribution-models", "title": "Available models", "description": "This section includes all available Attribution models used to process your data.", "bgColor": "pale-blue" }, { "url": "/docs/available-attribution-models", "title": "Available models", "description": "This section includes all available Attribution models used to process your data.", "bgColor": "siren", "textColor": "white" }, { "url": "/docs/available-attribution-models", "title": "Available models", "description": "This section includes all available Attribution models used to process your data." }, { "url": "/docs/available-attribution-models", "title": "Available models", "description": "This section includes all available Attribution models used to process your data.", "bgColor": "pale-yellow" } ] {%docs-links-end%}

Image modal

Accordion

{%docs-accordion title="How does Data Extraction work?"%}

Step 1. Step 1

Step 2. Step 2

{%docs-accordion-end%}

{%docs-accordion title="Solution"%}

When establishing a connection to your Google Big Query, the following error message is displayed:

{%docs-informer error%}

Checking connection failed: Access denied: Dataset <your-project-name>:<your-dataset>: Permission bigquery.tables.create denied on dataset <your-project-name>:<your-dataset> (or it may not exist).

{%docs-informer-end%}

{%docs-accordion-end%}