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Exploratory Data Analysis using Google Cloud Datalab

90m access · 60m completion
Connection Details

7 Credits

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01:30:00

Exploratory Data Analysis Using Google Cloud Datalab

GSP203

Google Cloud Self-Paced Labs

Overview

In this lab you will learn the process of analyzing a data set stored in Google BigQuery using Google Cloud Datalab to perform queries and present the data using various statistical plotting techniques. The analysis will help you discover patterns in the data that will allow you to predict probable arrival time delays given the initial flight details and actual departure time.

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

Google 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 GCP Quest.

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Score

—/10

Create a new Google Cloud Datalab instance.

Run Step

/ 5

Create a notebook into Cloud Datalab and Confirm that dataset named 'flights' exists.

Run Step

/ 5

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