Google BigQuery

Intermediate

LP Box Courses 2 Video Courses
LP Box quiz 1 Quiz Session
LP Box Lab No hands-on labs
Duration 1h 27m
Karma ~70 karma points
Certificate 441 students

Does your organization generate a huge amount of data every day? Does all of that data sit in a number of different databases, making it difficult to analyze? Even if you already have a data warehouse, can it keep up with your constantly growing volume of data? Google’s solution to these problems is Google BigQuery, a massive, lightning-fast data warehouse in the cloud.

This learning path will first show you the fundamentals of how to use BigQuery and then how to optimize BigQuery to reduce costs, speed up your queries, and apply proper access control.

Learning Objectives

  • Load data into BigQuery using files or by streaming one record at a time
  • Run a query using standard SQL and save your results to a table
  • Export data from BigQuery using Google Cloud Storage
  • Reduce your BigQuery costs by reducing the amount of data processed by your queries
  • Create, load, and query partitioned tables for daily time series data
  • Speed up your queries by using denormalized data structures, with or without nested repeated fields
  • Implement fine-grained access control using roles and authorized views 

So, if you’re interested in learning more about Google BigQuery, then click on the first course to get started!

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1

BigQuery is Google’s managed data warehouse in the cloud. BigQuery is incredibly fast. It can scan billions of rows in seconds. It’s also surprisingly inexpensive and easy to use. Querying terabytes of data costs only pennies and you only pay for what you use since there are no up-front costs. This is a hands-on course where you can follow along with the demos using your own Google Cloud account ...

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BigQuery is Google's incredibly fast, secure, and surprisingly inexpensive data warehouse, but there are ways to make it even faster, cheaper, and more secure. Here are some examples of what you will learn in this course: BigQuery can process billions of rows in seconds, but only if you break the rules of relational database design. If you are analyzing relatively small amounts of data, then your ...

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