Join Joseph Lowery for an in-depth discussion in this video Exporting data, part of Up and Running with Google Cloud Platform.
- Once you've analyzed your data,…the typical output is more data.…BigQuery makes working with your results…very straightforward whether you're…on own system or within BigQuery itself.…Let's start from the Google Cloud Console page…for my project and you can see because we just ran…a number of big queries there have been…some spikes in the activity.…Let me switch to one hour just to show you that.…Now to continue let's go to Big Data,…BigQuery and reopen that page.…
This time you'll see a list of all…the recent queries that we've made…including ones that generated an error.…Now when I hover over any of them, except…for the error one of course, I will see a lightning…bolt symbol over on the left and when I click…the query I'll get a little bit more information…about it including the query text,…when it ran, bytes process and so forth.…
If I want to see the results again,…all I have to do is click Run Query.…To work with this data, I have two options,…both conveniently grouped on the right…just above my results.…Let's check out the external file option first.…
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