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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: Uploading your own point data

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

In this tutorial, you will learn how to upload your own point data 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 properties

Before you can upload your Parquet files, you will have to tell the platform which properties to use and what each property represents

Step 3: Configure the processing settings

Configure the finest aggregation level for your point data.

Step 4: Upload the Parquet file

Now that the properties and the processing settings are configured, it is time to upload the Parquet file itself.

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 on how to use your data.

Tutorial: Uploading INRIX trips data

Step-by-step tutorial to learn how to upload INRIX trips data.
Goal

In this tutorial, you will learn how to upload floating vehicle data from INRIX. This data comes as waypoints CSV files and trips CSV files.

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

About INRIX trips data

Learn what INRIX trips data is, what the directory structure looks like, and what the file contents and most important properties are.

Uploading INRIX trips data

Learn how to create and configure a data set, upload the INRIX trips data using simple drag’n’drop of the waypoints and trips files.

Getting started using INRIX trips data

Learn how to use the INRIX trips data in your own projects and perform visual traffic analysis.

Tutorial: Analyzing traffic flows

Step-by-step tutorial to learn how to analyze traffic flows with floating vehicle data.
Goal

In this tutorial, you will learn how to analyze traffic flows using floating vehicle data. For example, to monitor the effectiveness of traffic diversions during roadworks.

At the end of this tutorial, you will have learned how to use the advanced space-time query language to compare traffic following different routes.

Roadworks, traffic diversions, and floating vehicle data

Learn the context of the example use-case and how floating vehicle data can be an extremely powerful data source for insight generation.

Setting up a traffic flow analysis project

Learn how to setup a new project and attach existing data to start a traffic flow analysis.

Analzying traffic flows using basic filters

Learn how to use the basic filtering for analyzing traffic flows.

At the end of this part, you will have learned how to filter on data attributes, how to filter data temporally, and how to use basic spatial filters.

Analzying traffic flows using advanced filters

Learn how to use the advanced filtering for analyzing traffic flows.

In this part of the tutorial, we will take the concrete use-case of the road block on the A45 and traffic diversions near Lüdenscheid in Germany and answer an example traffic analyst question using the advanced filtering capabilities.

Further reading

Now that you have learned how to analyze traffic flows, find additional resources to become a real traffic analysis expert.

Tutorial: Using the REST API with TypeScript

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

In this tutorial, you will learn how to use the REST API with TypeScript 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 first 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 and TypeScript.

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.

Known issues

List of known issues with the generated Typescript code, and their workaround

Tutorial: Using the REST API with Python

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

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

Generate Python code to interact with xyzt.ai

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

Setup and run your first API query with Python

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

Automating platform actions using the REST API with Python

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

Uploading data using the REST API with Python

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

Next steps

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