menu
arrow_back

Visualize Real Time Geospatial Data with Google Data Studio

Visualize Real Time Geospatial Data with Google Data Studio

1 ora 15 minuti 7 crediti

GSP201

Google Cloud Self-Paced Labs

Overview

This lab demonstrates how to use Google Dataflow to process real-time streaming data from a real-time real world historical data set, storing the results in BigQuery and then using Google Data Studio to visualize real-time geospatial data.

Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes via Java and Python APIs with the Apache Beam SDK. Cloud Dataflow provides a serverless architecture that can be used to shard and process very large batch data sets, or high volume live streams of data, in parallel.

BigQuery is a RESTful web service that enables interactive analysis of massively large datasets working in conjunction with Google Storage.

The data set that is used provides historic information about internal flights in the United States retrieved from the US Bureau of Transport Statistics website. This data set can be used to demonstrate a wide range of data science concepts and techniques and will be used in all of the other labs in the Data Science on Google Cloud Quest.

Crea un account Qwiklabs per leggere il resto del lab e tanto altro ancora.

  • Acquisisci accesso temporaneo a Google Cloud Console.
  • Oltre 200 lab dal livello iniziale a quelli più avanzati.
  • Corsi brevi per apprendere secondo i tuoi ritmi.
Crea un account per iniziare questo lab