![]() Material features online lectures, videos, demos, project work, readings and discussions. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story. Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. The following snippet represents a message a geofencing service sends to the TomTom Notifications API with this payload: 1 ". Whenever we use a contact group in multiple APIs, any change occurring inside this group's connectivity leads to a change in all APIs related to this group’s connections. Using these contact groups enables us to have single or multiple addresses. The TomTom Notifications API provides 20 webhook addresses per contact group. The request URL may look like the following: ![]() We do this using the group service called the create contact group endpoint. We get the key from our account dashboard.Īfter registering for an API Key, we should add a group with at least one way to send notifications. To start building our dataset, we first need a TomTom Maps API Key to work with the TomTom Notifications service. And, if your project expands, you can always pay as you grow. You get thousands of free requests - even for commercial applications. Getting Startedįirst, if you don’t already have a TomTom Developer account, register an account for free. ![]() This is a single file organized as a table of rows and columns. Although datasets come in various formats, such as a zip file or a folder containing multiple data tables, the simplest and most common dataset format is a CSV file. We then need to explore this intermediate data using analysis and visualization to understand it deeply and clearly. When we’re working on a data science project, we gather our information into a dataset. We’ll begin by creating a Python application that looks something like this: Building the Dataset Then, we’ll create some charts to visually inspect our data and gain helpful insights to improve driver efficiency. We’ll then import that bountiful data into Anaconda’s data science tools package. Let’s explore how to download TomTom mapping information to an Airtable database using Zapier and webhooks. This allows us to start filling a database with valuable data, like whenever a delivery vehicle or taxi driver crosses a geofence, for example. Webhooks are automated messages that send information when events happen. TomTom’s flexible Notifications API service enables emails or webhooks to send Maps API data to an application. When we import this data into our favorite analysis and visualization tools, we gain deep insights about more efficient routes and ways to make faster deliveries, or maybe even highlight an area your business can further develop. TomTom makes it easy to download the information we need. ![]() Map information is invaluable to data scientists working in taxi, delivery, logistics, and other industries. Pull TomTom's information into your favorite data science tools using webhooks and APIs, then visualize and analyze away! It's easy with just a bit of Python - learn how. ![]() Data scientists can access a wealth of mapping data to enhance their business insights. ![]()
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