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Tutorial: Getting started with the platform

Discover and play with all the main features of the platform by following a step-by-step tutorial
Introduction to maritime intelligence

Discover the capabilities of the platform to analyze movement data using maritime vessel AIS data.

The data used in this step-by-step tutorial contains positions and properties of ships, and our platform is used to extract insights from this data.

Suited for people with or without experience in the maritime industry.

Introduction to traffic analysis

Discover the capabilities of the platform to analyze movement data using floating vehicle data, typically used for traffic analysis.

The data used in this step-by-step tutorial contains positions and properties of cars, and our platform is used to extract insights from this data.

Suited for people with or without experience in the mobility industry.

Introduction to time series analysis

Discover the capabilities of the platform to analyze time series data using aggregated data for taxi trip statistics in New York.

The data used in this step-by-step tutorial contains aggregate taxi fare data for one year of pickups, and our platform is used to extract insights from this data.

Suited for people with or without experience in the mobility industry.

Tutorial: Uploading your own movement data

Step-by-step tutorial to learn how to work with your own movement data.
Goal

In this tutorial, you will learn how to upload your own movement data (.csv files) to the platform.

At the end of this tutorial, you will have created a new data set which can be used for analysis.

Step 0: Obtain data

Before we can start uploading data to the platform, we will need to acquire some data.

Step 1: Create data set

Your csv files are stored on the platform in a data set.

In this part, you will learn how to create such a data set.

Step 2: Define data structure

Before the platform can process your csv files, you will have to tell the platform about the structure of your data.

Step 3: Configure processing settings

In this part, you will learn how to configure the processing settings so that they match the accuracy of your data and your analytical requirements.

Step 4: Upload the csv files

Now that everything is configured, it is time to upload the .csv files.

Step 5: Use your data set

The data set is now ready to be used in a project.

Further reading

After finishing the data upload tutorial, discover the articles and tutorials on how to use your data.

Tutorial: Uploading your own time series data

Step-by-step tutorial to learn how to work with your own time series data.
Goal

In this tutorial, you will learn how to upload your own time series data (shapes as .geojson and time varying data as .csv files) to the platform.

At the end of this tutorial, you will have created a new data set which can be used for analysis.

Step 0: Obtain data

Before we can start uploading data to the platform, we will need to acquire some data.

Step 1: Create data set

Your files are stored on the platform in a data set.

In this part, you will learn how to create such a data set.

Step 2: Define the geojson properties

Before you can upload your GeoJSON files, you will have to tell the platform about what each property represents

Step 3: Upload the geojson file

Now that the GeoJSON properties are configured, it is time to upload the GeoJSON file itself.

Step 4: Define csv data structure

Before the platform can process your CSV files, you will have to tell the platform about the structure of your data.

Step 5: Upload the csv file

Now that everything is configured, it is time to upload the CSV files.

Step 6: Use your data set

The data set is now ready to be used in a project.

Further reading

After finishing the data upload tutorial, discover the articles and tutorials on how to use your data.

Tutorial: Using the REST API

Step-by-step tutorial to learn how to use the public REST API.
Goal

In this tutorial, you will learn how to use the REST API to automate project creation, attaching data sets to projects, creating dashboards, etc.

Generate Typescript code to interact with xyzt.ai

Use OpenAPI Generator to create convenience Typescript code to access the xyzt.ai REST API.

Setup and run your firsty API query

Use the generated Typescript code to interact with the xyzt.ai platform.

Automating platform actions using the REST API

Further automate tasks by creating a new project, attaching a data set, and creating a dashboard with the REST API.

Uploading data using the REST API

Create a new project by uploading data to the platform using the API.

Next steps

Now that you know how to use the API, explore the documentation to learn about data uploads, data queries, and more.