Skills you'll gain: Cloud Computing, Google Cloud Platform, Information Technology, Data Management, Databases, SQL, Statistical Programming, Big Data, Cloud Platforms, Cloud Storage, Computer Science, Data Science, Cloud Management, Computer Architecture, Data Analysis, Design and Product, Distributed Computing Architecture, Entrepreneurship, Exploratory Data Analysis, Full-Stack Web Development, Leadership and Management, Market Research, Marketing, Product Management, Product Marketing, Research and Design, Sales, Strategy and Operations, Web Development
Beginner · Course · 1-3 Months
Skills you'll gain: Cloud Computing, Google Cloud Platform, SQL, Databases, Cloud Platforms, Machine Learning, Information Technology, Computer Architecture, Data Management, Web Development, Distributed Computing Architecture, Entrepreneurship, Statistical Programming, Full-Stack Web Development, Cloud Storage, Business Psychology, Data Analysis, Data Analysis Software, Database Administration, Big Data, Computer Science, Data Science, Data Visualization, Cloud Management, Design and Product, Exploratory Data Analysis, Leadership and Management, Machine Learning Software, Market Research, Marketing, Product Management, Product Marketing, Research and Design, Sales, Strategy and Operations
Beginner · Specialization · 3-6 Months
Skills you'll gain: Databases, Cloud Computing, Cloud Platforms, Cloud Storage, Computer Architecture, Data Management, DevOps, Distributed Computing Architecture, Full-Stack Web Development, Google Cloud Platform, SQL, Statistical Programming, Web Development
Beginner · Project · Less Than 2 Hours
Skills you'll gain: Cloud Computing, Google Cloud Platform, Computer Architecture, Data Analysis, Data Management, Distributed Computing Architecture, Full-Stack Web Development, Web Development
Intermediate · Project · Less Than 2 Hours
Skills you'll gain: Cloud Computing, Google Cloud Platform, SQL, Databases, Cloud Storage, Computer Architecture, Data Analysis, Data Analysis Software, Database Administration, Distributed Computing Architecture, Cloud Management, Data Management, Full-Stack Web Development, Machine Learning Software, Statistical Programming, Web Development
Beginner · Course · 1-3 Months
Skills you'll gain: Cloud Computing, Cloud Platforms, Data Management, Google Cloud Platform, Big Data, Apache, Applied Machine Learning, Cloud Applications, Cloud Infrastructure, Cloud Storage, Data Analysis, Data Analysis Software, Data Architecture, Data Model, Data Structures, Data Warehousing, Database Application, Databases, Exploratory Data Analysis, Extract, Transform, Load, Machine Learning, Machine Learning Algorithms, Machine Learning Software, SQL
Beginner · Course · 1-3 Months
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.
Before learning BigQuery, it's very advantageous to have experience writing queries using SQL. You should also have experience using databases. You may also want to be familiar with the Google Cloud Platform and have experience with cloud computing.
Topics related to BigQuery that you can study include Google Sheets, Google Data Studio, data analytics, and the cloud. You might also be interested in learning about other big data tools, such as Redshift, DigitalOcean, S3, Apache Spark, Hadoop, and Hydra. Other technologies may also be of interest to you, such as TypeScript, auto-scaling clusters, Python, machine learning, and continuous deployment.
Places that hire people with a background in BigQuery include companies that are using BigQuery to manage and analyze their data. According to Google, this includes UPS, Twitter, Major League Baseball (MLB), The Home Depot, Dow Jones, Toyota, American Cancer Society, Target, 20th Century Fox, and many more. Companies in retail, financial services, media and entertainment, health care and life sciences, and government are just a few industries that hire people with a background in BigQuery across the world.
If you're a company, data scientist, data analyst, or individual looking for a platform that can analyze petabytes of data in the convenience of the cloud, learning BigQuery is a good fit for you. If your current data analytics processes run slower than you want or aren't giving you the data insights you need, learning BigQuery is worthwhile. BigQuery can help you manage and analyze marketing and sales data very quickly, for example. If that fits your needs, learning BigQuery may be right for you.