BigQuery is a serverless data warehouse that uses the Google Cloud platform. Data warehouses are critical components of data infrastructure required to collect and store data from a variety of sources for use within an organization, but building and maintaining warehouses at the scale necessary for today’s massive datasets can be expensive and time-consuming. By using cloud computing to enable rapidly-scalable analysis over petabytes of data, BigQuery is an important software as a service (SaaS) solution for companies looking to harness the power of big data flexibly and cost-effectively.

Like other relational database management systems (RDBMS), BigQuery uses the Structured Query Language or SQL to enable users to quickly store, retrieve, manage, and manipulate data. The Google Cloud platform also provides access to a variety of tools from Google and its partners, including Cloud Dataprep to automate the creation of data cleansing pipelines as well as built-in machine learning capabilities to generate insights from large-scale datasets. There are also a wide range of third-party tools that can be used with BigQuery for data visualization and other tasks.‎

A background in the use of BigQuery is an increasingly common requirement for a career as a data engineer. These specialized professionals in the creation and maintenance of data infrastructure are critical to the work of data science, which requires the delivery of massive datasets in a form that can be readily analyzed and utilized. And, like other cloud computing solutions, BigQuery is becoming popular with a growing number of tech companies due to its flexibility and cost-effectiveness compared to on premises data warehousing.

Given the fast-growing interest in using big data across virtually every industry, it’s no surprise that data engineer jobs are in high demand - and highly paid. According to Glassdoor, data engineers in the U.S. earn an average base pay of $102,864 per year.‎

Yes! In fact, Coursera lets you learn about BigQuery directly from Google itself. Google Cloud offers a variety of learning opportunities through the Coursera Platform, including individual courses in BigQuery specifically as well as Specializations that span multiple courses and topics including BigQuery skills. If you want to get a valuable career credential, you can even complete coursework for a Google Cloud Professional Data Engineer certification.

Regardless of your needs, the ability to study and complete course materials on your own schedule means that learning on Coursera is just as flexible - and powerful - as cloud computing-based SaaS solutions like BigQuery.‎