Connecting BI Analytics to BI systems

Using the BI Analytics API, you can connect your data to any BI platform and build custom reports, charts, and dashboards.

In this article, we will cover:

To view the BI Analytics API method structure, you can use the API documentation in Swagger format: BI API v1 — Swagger

In the Swagger documentation, you can:

view all available API methods
check the request and response structure
download the API specification in JSON format

How to enable BI Analytics access

Access to the BI Analytics API is configured at two levels:

1. Partner account level

2. User account level

To enable access, you need to:

Enable the Analytics Module for the partner
Enable the Analytics Module for the user's account
Add the bi_analytics = 1 configuration to the partner card

If you don't have access to the module settings or configuration on the partner account, please contact our support team.

1. Enable the Analytics module on the partner account

1. In the admin panel, go to the Partners section

2. Double-click on the selected partner — the partner card will open

3. Go to the Modules tab and enable the Analytics module

4. Next, go to the Configuration tab

5. Click the Add button

6. In the list, select the bi_analytics configuration and set its value to 1

7. Save your changes

2. Enable the Analytics module on the user's account

After enabling the module on the partner account, you also need to enable it for the specific user's account.

1. In the admin panel, find the required account

2. Right-click on it and select Edit

3. In the account card, go to the Modules tab

4. Enable the Analytics module

5. Save your changes

Once the Analytics module is enabled on both the partner account and the user's account, and the bi_analytics configuration is set — access to the BI Analytics API will be enabled.

The system will start collecting analytics data, and you will be able to connect to the API through Power BI.

Where to get your login and password

To connect to the BI Analytics API, you need the partner account login and password.

Use the same credentials that were provided when the partner account was registered. These are the same login details used to sign in to the admin panel.

If you have main administrator access, you can find these credentials in the partner account card under the Main settings tab:

Login — use as username
Password — use as password

How to choose the server address

To connect to BI Analytics API, you need to specify the server address in the BaseUrl parameter in the query. Use the server where your account is hosted.

Server	Address	Purpose
Production	https://pilot-gps.com	Main server
Saudi Arabia	https://ksa.pilot-gps.com	Regional server for Saudi Arabia
Africa	https://pilot-gps.africa	Regional server for Africa
Blade	https://blade.pilot-gps.com	Blade server
Iglit	https://gps.iglit.tech	Iglit server

In the query, specify the required URL, for example:

BaseUrl = "https://ksa.pilot-gps.com",

Request limits

To keep the system stable, BI Analytics API has request limits.

Default limits

These limits apply by default if the bi_analytics_limit parameter is not set:

100 requests per hour
2000 requests per day
50000 requests per month (30 days)

How to connect BI Analytics in Power BI

Below is an example of connecting via Microsoft Power BI. The same approach can be used with any BI system that supports REST API.

How to add a query in Power BI

1. Open Power BI Desktop

Launch Power BI Desktop on your computer. If it is not installed, download it for free from the official Microsoft website.

2. On the main toolbar at the top, click the Get Data button. A list of available data sources will appear

3. From the list of data sources, select Blank query

4. The Power query editor will open. This is the window where queries are created and configured.

In this window, find the Advanced editor button on the top toolbar and click it.

5. The Advanced editor window will open with an empty query template.

6. Paste the query code into the editor. See the example query below

In the query, you need to specify:

Server address — the URL of your server
Login — your login from the partner account
Password — your password from the partner account
Dates — the start and end dates of the period
List of metrics — which data you want to retrieve (see the full list of metrics below)

7. After pasting the code, click Done

Power BI will start connecting to the server and loading data.

8. After that, Power BI may display the warning “Information is required about data privacy”. Click Continue.

9. The Privacy levels window will open.

In this window, Power BI checks whether it can safely combine and process data from the sources used in the query. In our case, the query uses one trusted data source, and authorization is already handled inside the query itself. To prevent Power BI from blocking the load or interfering with query execution, check: Ignore privacy levels checks for this file.

Then click Save.

10. After saving, Power BI will execute the query and open a data preview in Power query editor.

You will see a table with rows and columns — this is the data returned by your query.

11. Click Close & Apply. After that, the data will be loaded into Power BI, and you can start working with it.

Now you can use the loaded data to create charts, tables, and other visual elements.

In the main Power BI Desktop window, the following panels are usually displayed on the right:

Visualizations — contains chart types, diagrams, cards, tables, and other visual elements. Choose the type you need, then fill it with your fields
Data — shows the list of tables and fields loaded from your query, such as date, object ID, mileage, fuel consumption, and average speed. You can use these fields in visualizations by selecting them with checkboxes, dragging them with the mouse, or rearranging them
Filters — lets you limit data using the conditions you need

How to build a chart

1. In the Visualizations panel, click the chart type you need. A blank chart template will appear on the report canvas

2. In the Data panel, select the fields you want to display

3. Power BI will automatically place the selected fields into the chart.

In Power BI, you can combine data in different ways:

add the same field to multiple charts
compare several indicators
build multiple visualizations on one page
replace fields without recreating the report from scratch

If the query doesn't update or you get login errors

Sometimes Power BI saves the previous connection settings for a data source. Even if you change the login, password, or server address, the query may keep returning an authorization error because Power BI is still using the old credentials. In this case, you need to clear the saved permissions so that Power BI asks for the credentials again.

How to clear permissions

1. In the Power Query Editor, click Data source settings on the toolbar

2. In the window that opens, select the data source you need — for example, your server address

1 — Button Data source settings

2 — Select your data source

3 — Button Clear Permissions

3. Click Clear Permissions

4. In the confirmation window, click Delete

5. Run the query again. Power BI will reapply the connection settings with the new credentials.

Example request for a BI system

let

BaseUrl = "https://<server_address>,

LoginJson =

Json.Document(

Web.Contents(

BaseUrl,

[

RelativePath = "api/bi/login.php",

Headers = [#"Content-Type" = "application/json"],

Content = Json.FromValue([

username = "YOUR_LOGIN",

password = "YOUR_PASSWORD"

]),

ManualStatusHandling = {400, 401, 403, 404, 500}

]

)

Token = LoginJson[access_token],

NodeId = LoginJson[user][node_id],

AnalyticsJson =

Json.Document(

Web.Contents(

BaseUrl,

[

RelativePath = "api/bi/analytics.php",

Query = [node = Text.From(NodeId)],

Headers = [

#"Authorization" = "Bearer " & Token,

#"Content-Type" = "application/json"

Content = Json.FromValue([

date_from = "2026-01-01",

date_to = "2026-12-31",

metrics = {

"veh_driving_dist",

"veh_fuel_cons",

"average_speed",

"veh_cars_counter"

source = "vehicle",

group_by = "source_day",

format = "flat"

]),

ManualStatusHandling = {400, 401, 403, 404, 500},

ExcludedFromCacheKey = {"Authorization"}

]

)

DataList = AnalyticsJson[data],

Tbl = Table.FromList(DataList, Splitter.SplitByNothing(), {"Column1"}),

Expanded = Table.ExpandRecordColumn(

Tbl,

"Column1",

{"source_id", "date", "veh_driving_dist", "veh_fuel_cons", "average_speed", "veh_cars_counter"}

)

Expanded

Main query parameters

source

The source field defines which data the query should use.

Available values:

vehicle — vehicle data
driver — driver data

group_by

The group_by field defines how the result is grouped.

Value	What it shows	Example response structure
total	Total for all vehicles or drivers for the selected period	{ "metric": 123 }
day	Total for all vehicles or drivers for each day	{ "20260301": { "metric": 123 } }
rating	Each source, total for the selected period	{ source_id: { "metric": 123 } }
source_day	Each source, each day	{ source_id: { "20260301": { "metric": 123 } } }

ACCOUNT_ID

The ACCOUNT_ID parameter allows you to limit the data export to a single account.

If the query uses the partner account login and password without ACCOUNT_ID, the system will export all vehicles across all accounts available to that partner.

If you specify ACCOUNT_ID in the query, only the objects from the selected account will be loaded.

Available metrics

Below is the list of parameters you can use in the metrics field.

Vehicle — general

Parameter	Description
veh_trips_cnt	Number of trips
veh_driving_dist	Mileage (km)
veh_driving_time	Driving time
veh_parking_time	Parking time
veh_ignition_time	Ignition on time
veh_idle_time	Idle time
veh_motor_hours	Engine hours

Vehicle — fuel

Parameter	Description
veh_fuel_cons	Fuel consumption
veh_fuel_filled	Fuel filled
veh_fuel_drained	Fuel drained

Vehicle — violations

Parameter	Description
veh_eco_fine	Eco-driving fine
veh_eco_cnt	Number of eco-driving violations
veh_acc_fine	Harsh acceleration fine
veh_acc_cnt	Number of harsh accelerations
veh_braking_fine	Harsh braking fine
veh_braking_cnt	Number of harsh braking events
veh_turn_fine	Harsh turn fine
veh_turn_cnt	Number of harsh turns
veh_speed_fine	Speeding fine
veh_speed_cnt	Number of speeding events
veh_belt_fine	Seat belt violation fine
veh_belt_cnt	Number of seat belt violations
veh_idle_fine	Idle fine
veh_idle_cnt	Number of idle violations

Vehicle — costs

Parameter	Description
veh_fuel_cost_per_kilometer	Fuel cost per km
veh_service_cost_per_kilometer	Service cost per km
veh_amount_exp	Total expenses
cost_of_using	Cost of use
average_speed	Average speed
veh_cars_counter	Number of vehicles

Drivers

Parameter	Description
drv_trips_cnt	Number of trips
drv_driving_dist	Mileage (km)
drv_driving_time	Driving time
drv_parking_time	Parking time
drv_fuel_cons	Fuel consumption
drv_fuel_filled	Fuel filled
drv_fuel_drained	Fuel drained
drv_eco_fine	Eco-driving fine
drv_eco_cnt	Number of eco-driving violations
drv_acc_fine	Harsh acceleration fine
drv_acc_cnt	Number of harsh accelerations
drv_braking_fine	Harsh braking fine
drv_braking_cnt	Number of harsh braking events
drv_turn_fine	Harsh turn fine
drv_turn_cnt	Number of harsh turns
drv_speed_fine	Speeding fine
drv_speed_cnt	Number of speeding events
drv_belt_fine	Seat belt violation fine
drv_belt_cnt	Number of seat belt violations

Custom eco metrics

For eco events, you can use the following template:

eco_{N}_fine
eco_{N}_cnt

where N is the ID of the eco event type in the system.

Examples

Parameter	Description
eco_4_fine / eco_4_cnt	Eco violations of type 4
eco_8_fine / eco_8_cnt	Eco violations of type 8
eco_17_fine / eco_17_cnt	Eco violations of type 17