Join Joseph Lowery for an in-depth discussion in this video Loading data, part of Up and Running with Google Cloud Platform.
- View Offline
- In this lesson, we'll create a dataset…to be used by BigQuery.…I've compiled a list of the most popular baby names,…as recorded by the U.S. government,…from 2003 to 2013 for our demo.…Let's start by looking at the CSV file in Excel.…You can find this file in the Exercise Files…Chapter 3, 03_02, Start folder.…It's called baby_names.csv.…As you can see, it's a pretty simple file.…There are four columns: Name, Gender, Frequency and Year.…
If I hit Command End to go to the end of the file,…you can see that there are 368,840 rows.…Maybe not massive, but darn big.…Okay, let's switch to the Google Cloud Console…and click on the project name,…drill down to, in our case, Lynda Cloud 1.…Once that opens up, go to BigData in the navigation,…and then choose BigQuery.…You'll notice there's an external file icon here.…
BigQuery has a slightly different user interface…that's not quite integrated into the rest…of the Google Cloud Platform at this point,…but it's still very effective, so I'll click that.…And here, you can take BigQuery for a spin…
Learn the basics of hosting a mobile app with App Engine and see how to analyze massive datasets in seconds with BigQuery. Then explore the benefits of Cloud Storage, including unlimited file storage and fast data retrieval, and learn how to establish a cloud-based private network with Compute Engine. Finally, the course explores how to set up and manage cloud-based databases with Cloud Datastore and Cloud SQL.
- Why Google Cloud Platform?
- Deploying an app with Google App Engine
- Activating and working with Google Cloud Storage
- Loading, querying, and exporting data with BigQuery
- Working with Cloud Storage buckets
- Managing cloud-based private networks
- Importing and exporting data
- Scheduling backups
- Working with Google Datastore
- Filtering data with Cloud SQL